Canadian Doctors and Former Microsoft Canada President Warn About Grave Health Risks of 5G


The telecom industry has provided no scientific evidence that 5G is safe and there is research that already proves it isn’t (see 1, 2).  Because of this, some government leaders have already declared moratoriums on installation (see 1, 2, 3).

Additional warnings about 5G have come from a variety of sources including:

  1. Meteorologists who fear that 5G frequencies will greatly reduce their ability to accurately predict the weather.
  2. Utility companies fear that 5G will interfere with their already problematic Smart Grids and Smart Meters.
  3. Security experts fear cyberattacks on the easily hacked 5G and Internet of Things (IoT) technologies could lead to catastrophic consequences (see 1, 2).

Unfortunately, this hasn’t stopped 5G installation everywhere – including in Canada – despite publicized opposition from doctors, scientists, and former Microsoft Canada president, Frank Clegg.

If the telecom industry won’t even defend 5G, shouldn’t we be concerned about anyone who does?

Watch the video.

URL:https://youtu.be/-T2R2htAaqg

For more information, visit the following websites:

This Radical New DNA Microscope Reimagines the Cellular World


It’s not every day that something from the 17th century gets radically reinvented.

But this month, a team from the Broad Institute at MIT and Harvard took aim at one of the most iconic pieces of lab ware—the microscope—and tore down the entire concept to recreate it from scratch.

rainbow cell segmentation in DNA microscopy biotechnology

I’m sure you have a mental picture of a scope: a stage to put samples on, a bunch of dials to focus the image, tunnel-like objectives with optical bits, an eyepiece to observe the final blown-up image. Got it? Now erase all that from your mind.

The new technique, dubbed DNA microscopy, uses only a pipette and some liquid reagents. Rather than monitoring photons, here the team relies on “bar codes” that chemically tag onto biomolecules. Like cell phone towers, the tags amplify, broadcasting their signals outward. An algorithm can then piece together the captured location data and transform those GPS-like digits into rainbow-colored photos.

The results are absolutely breathtaking. Cells shine like stars in a nebula, each pseudo-colored according to their genomic profiles.

That’s the crux: DNA microscopy isn’t here to replace its classic optical big brother. Rather, it pulls the viewer down to a molecular scale, allowing you to see things from the “eyes of the cell,” said study author Dr. Joshua Weinstein, who worked under the supervision of Dr. Aviv Regev and Dr. Feng Zhang, both Howard Hughes Medical Institute investigators.

The tech decodes the natural location of molecules inside a cell—and how they interact—while simultaneously gathering information about its gene expression in a two-in-one combo. It’s a bonanza for scientists struggling to tease apart individual differences in cells that physically look identical—say, immune cells that secrete different antibodies, or cancer cells in their early stage of malignant transformation.

“It’s a completely new way of visualizing biology,” said Weinstein in a press release. “This gives us another layer of biology that we haven’t been able to see.”

Why?

Almost all current microscopy techniques stem from the original all-in-one light microscope, first introduced in the 17th century. The core concept is light: the device guides photons refracted from the sample into a series of mirrors and optical lenses, resulting in an enlarged image of whatever you’re focusing on. It basically works like a DSLR camera with a very powerful zoom lens.

Scientists have long since moved past the visible light spectrum. Electron microscopy, for example, measures electrons that bounce off tissue to look at components inside the cell. Fluorescent microscopy—the “crown prince” of imaging—captures emitted light waves after stimulating tissue-bound fluorescent probes with lasers.

But here’s the thing: even as traditional microscopy is increasingly perfected and streamlined, it hits two hard limits. One is resolution. Light scatters, and there’s only so much we can do to focus the beam on one point to generate a clear image. This is why a light microscope can’t clearly see DNA molecules or proteins—it’s like using a smartphone to capture a single bright star. As a result, current microscopes generate satellite views of goings-on on the cellular “Earth.” Sharp, but from afar.

The second is genomic profiling. There’s been a revolution in mapping cellular diversity to uncover how visually similar cells can harbor dramatically different genomic profiles. A perfect example is the immune system. Immune cells that look similar can secrete vastly different antibodies, or generate different protein “arms” on their surface to grab onto specific types of cancer cells. Sequencing the cells’ DNA loses spatial information, making it hard to tease out whether location is important for designing treatments.

So far, microscopy has only focused on half of the picture. With DNA microscopy, the team hopes to grab the entire landscape.

“It will allow us to see how genetically unique cells—those comprising the immune system, cancer, or the gut, for instance—interact with one another and give rise to complex multicellular life,” explained Weinstein.

Inner Workings

To build their chemical microscope, the team began with a group of cultured cells.

They decoded the cells’ RNA molecules and transcribed the data to generate a complete library of expressed genes called cDNA. Based on cDNA sequences, they then synthesized a handful of tags randomly made of the DNA letters A, T, C, and G, each about 30 letters long. When bathed onto a new batch of cells, the tags tunneled inside and latched onto specific RNA molecules, labeling each with a specific barcode.

To amplify individual signals—each “point source”—the team used a common chemical reaction that rapidly amplifies DNA molecules, increasing their local concentration. DNA doesn’t like staying put inside the liquid interior of a cell, so the tags slowly begin to drift outwards, like a drop of dye expanding in a pool of water. Eventually, the DNA tags balloon into a molecular cloud that stems from their initial source on the biomolecule.

“Think of it as a radio tower broadcasting its signal,” the authors explained.

As DNA tag clouds from multiple points grow, eventually they’ll collide. This triggers a second reaction: two diffusing DNA molecules physically link up, spawning a unique DNA label that journals their date. This clever hack allows researchers to eventually triangulate the location of the initial sources: the closer the two points are in the beginning, the more labels they’ll form. The further apart, the fewer. The idea is very similar to cell phone companies using radio towers to track their users’ locations, in which they measure where signals from three or more towers intersect.

The cells are subsequently collected and their DNA extracted and sequenced—something that takes roughly 30 hours. The data is then decoded using a custom algorithm to transform raw data into gorgeous images. This is seriously nuts: the algorithm has absolutely no clue what a “cell” is, but still identified individual cells at their location inside the sample.

“The first time I saw a DNA microscopy image, it blew me away,” said Regev.

As proof of concept, the team used the technique to track cells that encode either green or red fluorescent proteins. Without any previous knowledge of their distribution, the DNA microscope efficiently parsed the two cell types, although the final images were blurrier than that obtained with a light microscope. The tech could also reliably map the location of individual human cancer cells by tagging the cells’ internal RNA molecules, although it couldn’t parse out fine details inside the cell.

A Whole New World

Thanks to DNA’s “stickiness,” the technique can be used to label multiple types of biomolecules, allowing researchers to track the location of and identify antibodies or surface proteins on any given cell type, although the team will have to further prove its effectiveness in tissue samples.

Although the resolution of DNA microscopy is currently on par, if not slightly lower than, that of a light microscope, it provides an entirely new perspective of biomolecules inside cells.

“We’ve used DNA in a way that’s mathematically similar to photons in light microscopy. This allows us to visualize biology as cells see it and not as the human eye does,” said Weinstein.

DNA microscopy already does things a light microscope can’t. It can parse out cells that visually look similar but have different genetic profiles, for example, which comes in handy for identifying various types of cancer and immune cells. Another example is neuroscience: as our brains develop, various cells drastically alter their genetic profiles while migrating long distances—DNA microscopy could allow researchers to precisely track their movements, potentially uncovering new ways to boost neuroregeneration or plasticity.

Only time will tell if DNA microscopy will reveal “previously inaccessible layers of information,” as the team hopes. But they believe that their invention will spark new ideas and uses in the scientific community.

“It’s not just a new technique, it’s a way of doing things that we haven’t ever considered doing before,” said Regev.

New Markers For Alzheimer’s Disease Could Aid Diagnosis And Speed Up Drug Development


The squiggly blue lines visible in the neurons are an Alzheimer’s biomarker called tau. The brownish clumps are amyloid plaques.

Courtesy of the National Institute on Aging/National Institutes of Health

Alzheimer’s disease begins altering the brain long before it affects memory and thinking.

So scientists are developing a range of tests to detect these changes in the brain, which include an increase in toxic proteins, inflammation and damage to the connections between brain cells.

The tests rely on biomarkers, shorthand for biological markers, that signal steps along the progression of disease. These new tests are already making Alzheimer’s diagnosis more accurate, and helping pharmaceutical companies test new drugs.

“For the future, we hope that we might be able to use these biomarkers in order to stop or delay the memory changes from ever happening,” says Maria Carrillo, chief science officer of the Alzheimer’s Association. (The association is a recent NPR sponsor.)

The first Alzheimer’s biomarker test was approved by the Food and Drug Administration in in 2012.

It’s a dye called Amyvid that reveals clumps of a protein called amyloid. These amyloid plaques are a hallmark of Alzheimer’s.

Before Amyvid came along, diagnosing the disease involved a lot of guesswork, says Dr. Howard Fillit, founding executive director and chief science officer at the Alzheimer’s Drug Discovery Foundation.

“I can now send a patient down the block to the radiology office and within 24 hours with 98% certainty I can tell people if they have Alzheimer’s disease,” Fillit says.

The test costs thousands of dollars, though, in part because it requires a PET scan of the brain. Also, Amyvid reveals only amyloid plaques, which are just one of the brain changes associated with Alzheimer’s.

So the Alzheimer’s Drug Discovery Foundation has launched an effort to speed up development of biomarkers that are cheaper and detect a wider range of brain changes.

One promising test detects the protein tau, which causes toxic tangles to form inside brain cells.

“The tangles represent the dying neurons,” Fillit says, which means a biomarker for tau could make diagnosing Alzheimer’s even more accurate. It could also help pharmaceutical companies assess experimental drugs meant to remove tau from the brain.

Several drug companies appear close to receiving FDA approval for injected dyes that reveal tau in patients who get PET scans.

And eventually, scientists hope to use biomarkers in spinal fluid and blood to assess levels of both amyloid and tau in the brain. Those tests promise to be easier for patients, and less expensive to administer.

But even detecting amyloid and tau in the brain won’t be enough, Fillit says. People can have high levels of both and still do pretty well until something else shows up in the brain: inflammation.

“It’s like having the highest sensitivity computer up there and throwing coffee on it,” Fillit says.

So researchers are working to identify biomarkers for inflammation.

They’re also working on a biomarker that indicates the health of synapses, the connections between brain cells.

Weakening synapses are one of the surest signs of Alzheimer’s, Fillit says. “So we’re funding a clinical trial at a company that is going to use this biomarker as a measure of how well their drug is preserving synapses in the hippocampus of people with Alzheimer’s disease.”

Biomarkers for Alzheimer’s are still a work in progress. For example, they will have to be tested in many different populations.

“What may represent as a biomarker in one population may not actually hold true in another, and we’ve seen this in other diseases,” says the Alzheimer Association’s Carrillo.

Also, biomarkers still don’t offer a reliable way to measure a person’s mental function. They only reveal the brain changes that are associated with loss of memory and difficulty thinking.

Even so, over time the arrival of new markers should make treating Alzheimer’s more like treating other diseases, Carrillo says.

“We treat high cholesterol to reduce the risk of that heart attack,” she says. And someday it may be possible to reduce the risk of dementia by treating high levels of amyloid, tau or inflammation in the brain.

Scientists Can Now Clone Brain Organoids. Here’s Why That Matters


An army of free-floating minibrain clones are heading your way!

No, that’s not the premise of a classic sci-fi brain-in-jars blockbuster. Rather, a team at Harvard has figured out a way to “clone” brain organoids, in the sense that every brain blob, regardless of what type of stem cell it originated from, developed nearly identically into tissues that mimic the fetal human cortex. No, they didn’t copy-paste one minibrain to make a bunch more—rather, the team found a recipe to reliably cook up hundreds of 3D brain models with very little variability in their cellular constituents.

If that sounds like a big ole “meh,” think of it like this. Minibrains, much like the organs they imitate, are delicate snowflakes, each with their own unique cellular makeup. Sure, no two human brains are exactly the same, even those of twins. However, our noggins do follow a relatively set pathway in initial development and end up with predictable structures, cell types, and connections.

Not so for minibrains. “Until now, each … makes its own special mix of cell types in a way that could not have been predicted at the outset,” explained study author Dr. Paola Arlotta. By compiling a cellular atlas from multiple minibrains, her team basically found a blueprint that coaxes stem cells from different genetic and gender origins to mature into remarkably similar structures, at least in terms of cellular composition. Putting it another way, they farmed a bunch of identical siblings; but rather than people, they’re free-floating brain blobs.

Rest assured, it’s not a new evil-scientist-brain-control scheme. For brain organoids to be useful in neuroscience—for example, understanding how autism or schizophrenia emerge—scientists need large amounts of near-identical test subjects. This is why twins are extremely valuable in research: all else (nearly) equal, they help isolate the effects of individual treatments or environmental changes.

“It is now possible to compare ‘control’ organoids with ones we create with mutations we know to be associated with the disease,” said Arlotta. “This will give us a lot more certainty about which differences are meaningful.”

How to Grow a Brain

The authors set out with a slightly different question in mind: is it possible to reliably grow a brain outside the womb?

You may be asking “why not?” After all, scientists have been cooking up brain organoids for half a decade. But although specific instructions are generally similar, the resulting minibrains—not so much.

Here’s the classic recipe. Scientists start with harvested stem cells, embed them into gel-like scaffolds, then carefully nurture them in a chemical soup tailored to push the cells to divide, migrate, and mature into tiny balls. These tissue nuggets are then transferred to a slow spinning bioreactor—imagine a giant high-tech smoothie machine. The gentle whirling motion keeps the liquid nicely oxygenated. In six months, the grains of greyish tissue expand to a few millimeters, or one-tenth of the width of your finger, packed full with interconnected brain cells.

This is the “throw all ingredients into a pot and see what happens” approach, more academically known as the unguided method. Because scientists don’t interfere with the brain balls’ growth, the protocol gives stem cells the most freedom to self-organize. It also allows stem cells to stochastically choose what type of brain cell—neurons, glia, immune cells—they eventually become. God may not play dice, but outside the womb, stem cells sure do.

That’s problematic. Depending on the initial stem cell population, the culture conditions, and even the particular batch, the resulting minibrains end up with highly unpredictable proportions of cell types arranged in unique ways. This makes controlled experimenting with minibrains extremely difficult, which nixes their whole raison d’être.

Similar to their human counterparts, unguided minibrains also follow the instructions laid out in their DNA. So what gives?

Our brains do not grow in isolation. Rather, they’re guided by a myriad of local chemical messengers, hormones, and mechanical forces in the womb—all of which are devoid inside the spinning bioreactor. A more recent way to grow brain blobs is the guided method: scientists add a slew of “external patterning factors” at a very early stage of development, when stem cells first begin to choose their fate. These factors are basically biological fairy dust that push minibrain structures into a particular “pattern,” essentially sealing their fate.

Brain organoids grown this way are generally more consistent in cellular architecture once they mature. For example, many consistently develop the multi-striped pattern characteristic of the cerebral cortex—the outermost layer of the brain involved in sensation, reasoning, and other higher cognitive functions. But do they also resemble each other in their cellular makeup?

Reliable Brain Farming

The team first used both approaches to foster several dozen minibrains for half a year. They began with multiple types of stem cells from both male and female donors: induced pluripotent stem cells, which are skin cells returned to a youth-like stage, immortal human embryonic stem cells, and others.

They then carefully analyzed the resulting brainoids’ genetic makeup at multiple time points to track their growth. The team tapped an extremely powerful—and increasingly popular—tool called single-cell RNA sequencing, which provides invaluable insight into gene expression in every single cell.

In all, they parsed the genetic fingerprints of over 100,000 cells from 21 organoids, and matched those data to existing databases to tease out the cells’ identities. Finally, the team mapped out the distribution of each cell type in every analyzed organoid.

Unsurprisingly, those grown with the unguided method had cellular profiles all over the place. But with the guided approach—particularly, ones dubbed the “dorsally patterned” type—95 percent were “virtually indistinguishable” in their cellular compendium. What’s more, these minibrains also followed incredibly similar development trajectories, in that different cell types popped up at near-identical time points. Even their cellular origin didn’t matter: organoids grown from different stem cells were consistent in their final cellular inhabitants.

Conclusion? The embryo isn’t required for our brain to produce all its cellular diversity; it’s totally possible to reliably grow brainoids outside the womb.

CRISPRed Minibrains?

The results are a huge boon for studying neurological diseases such as autism, epilepsy, and schizophrenia. Scientists believe that the root cause of these complex disorders lies somewhere in the tangled dance of fetal brain growth. So far, a clear cause has been elusive.

Using the guided “dorsally patterned” recipe, teams can now grow organoids from stem cells derived from patients, or genetically engineer pathological mutations to study their effects. Because the study proves minibrains made this way are remarkably similar, researchers will be able to nail down risk factors—and test potential treatments—without worrying about biological noise stemming from minibrain diversity.

Arlotta is already exploring possibilities. Using CRISPR, she plans to edit genes potentially linked to autism in stem cells, and grow them out as minibrains. Using the same technique, she can also make “control” organoids as a baseline for her experiments.

We can now “move much more swiftly towards concrete interventions, because they will direct us to the specific genetic features that give rise to the disease,” she said. “We will be able to ask far more precise questions about what goes wrong in the context of psychiatric illness.”

Oncologists are guardedly optimistic about AI. But will it drive real improvements in cancer care?


Over the course of my 25-year career as an oncologist, I’ve witnessed a lot of great ideas that improved the quality of cancer care delivery along with many more that didn’t materialize or were promises unfulfilled. I keep wondering which of those camps artificial intelligence will fall into.

Hardly a day goes by when I don’t read of some new AI-based tool in development to advance the diagnosis or treatment of disease. Will AI be just another flash in the pan or will it drive real improvements in the quality and cost of care? And how are health care providers viewing this technological development in light of previous disappointments?

To get a better handle on the collective “take” on artificial intelligence for cancer care, my colleagues and I at Cardinal Health Specialty Solutions fielded a survey of more than 180 oncologists. The results, published in our June 2019 Oncology Insights report, reveal valuable insights on how oncologists view the potential opportunities to leverage AI in their practices.

Limited familiarity tinged with optimism. Although only 5% of responding oncologists describe themselves as being “very familiar” with the use of artificial intelligence and machine learning in health care, 36% said they believe it will have a significant impact in cancer care over the next few years, with a considerable number of practices likely to adopt artificial intelligence tools.

The survey also suggests a strong sense of optimism about the impact that AI tools may have on the future: 53% of respondents said that such tools are likely or very likely to improve the quality of care in three years or more, 58% said they are likely or very likely to drive operational efficiencies, and 57% said they are likely or very likely to improve clinical outcomes. In addition, 53% described themselves as “excited” to see what role AI will play in supporting care.

An age gap on costs. The oncologists surveyed were somewhat skeptical that AI will help reduce overall health care costs: 47% said it is likely or very likely to lower costs, while 23% said it was unlikely or very unlikely to do so. Younger providers were more optimistic on this issue than their older peers. Fifty-eight percent of those under age 40 indicated that AI was likely to lower costs versus 44% of providers over the age of 60. This may be a reflection of the disappointments that older physicians have experienced with other technologies that promised cost savings but failed to deliver.

Hopes that artificial intelligence will reduce administrative work. At a time when physicians spend nearly half of their practice time on electronic medical records, we were not surprised to see that, when asked about the most valuable benefit that AI could deliver to their practice, the top response (37%) was “automating administrative tasks so I can focus on patients.” This response aligns with research we conducted last year showing that oncologists need extra hours to complete work in the electronic medical record on a weekly basis and the EMR is one of the top factors contributing to stress at work. Clearly there is pent-up demand for tools that can reduce the administrative burdens on providers. If AI can deliver effective solutions, it could be widely embraced.

Need for decision-support tools. Oncologists have historically been reluctant to relinquish control over patient treatment decisions to tools like clinical pathways that have been developed to improve outcomes and lower costs. Yet, with 63 new cancer drugs launched in the past five years and hundreds more in the pipeline, the complexity surrounding treatment decisions has reached a tipping point. Oncologists are beginning to acknowledge that more point-of-care decision support tools will be needed to deliver the best patient outcomes. This was reflected in our survey, with 26% of respondents saying that artificial intelligence could most improve cancer care by helping determine the best treatment paths for patients.

AI-based tools that enable providers to remain in control of care while also providing better insights may be among the first to be adopted, especially those that can help quickly identify patients at risk of poor outcomes so physicians can intervene sooner. But technology developers will need to be prepared with clinical data demonstrating the effectiveness of these tools — 27% of survey respondents said the lack of clinical evidence is one of their top concerns about AI.

Challenges to adoption. While optimistic about the potential benefits of AI tools, oncologists also acknowledge they don’t fully understand AI yet. Fifty-three percent of those surveyed described themselves as “not very familiar” with the use of AI in health care and, when asked to cite their top concerns, 27% indicated that they don’t know enough to implement it effectively. Provider education and training on AI-based tools will be keys to their successful uptake.

The main take-home lesson for health care technology developers from our survey is to develop and launch artificial intelligence tools thoughtfully after taking steps to understand the needs of health care providers and investing time in their education and training. Without those steps, AI may become just another here today, gone tomorrow health care technology story.

Medical IDs: Enemy of Privacy, Liberty, and Health


Ron Paul exposes the dark side of the new American medical ID system which the House of Representatives voted in favor of in a Labor, Health and Human Services, and Education appropriations bill amendment.

[GreenMedInfo.com Editor’s note: one of the primary reasons mandatory vaccination can not be practically instituted is because there is, at present, no objective way to verify a citizen’s vaccine record. This medical ID system would change that, making it entirely possible to require a citizen to provide authorities the digital equivalent of their “vaccine papers,” and those who fall short forced to comply with the ever-expanding vaccine schedule, or face fines, imprisonment or quarantine.]

Last week, the House of Representatives voted in favor of a Labor, Health and Human Services, and Education appropriations bill amendment to repeal the prohibition on the use of federal funds to create a “unique patient identifier.” Unless this prohibition, which I originally sponsored in 1998, is reinstated, the federal government will have the authority to assign every American a medical ID. This ID will be used to store and track every American’s medical history.

A unique patient identifier would allow federal bureaucrats and government-favored special interests to access health information simply by entering an individual’s unique patient ID into a database. This system would also facilitate the collection of health information without a warrant by surveillance state operatives.

The health records database could easily be linked to other similar databases, such as those containing gun purchase records or education records. If mandatory E-Verify becomes law, the health records database could even be linked to it, allowing employers to examine a potential employee’s medical history.

The possibility that the unique patient identifier system may be linked to a database containing information regarding gun ownership is especially disturbing given the bipartisan support for “red flag” laws. These laws allow the government to deny respect for someone’s Second Amendment rights without due process and based solely on an allegation that the individual is mentally unstable and likely to commit an act of gun violence. Combining red flag laws with the unique patient identifier system would leave a gun owner who ever sought psychiatric help for any reason at risk of losing his ability to legally possess a gun.

Unscrupulous government officials could use medical information to harass those whose political activities challenge the status quo. Anyone who doubts this should ask themselves what a future J. Edgar Hoover or Lois Lerner would do with access to the medical information of those involved in political movements he wishes to silence.

The unique patient identifier undermines one of the foundations of quality health care: the doctor-patient relationship. Accurate diagnosis requires that patients share intimate details about their lives — ranging from details about their diet and exercise habits to their sexual history and alcohol and drug use — with their physicians. If patients legitimately fear information shared will be compromised, they will be unwilling to be completely honest with their physicians, making it impossible for physicians to effectively treat their patients.

Proponents of the unique patient identifier claim it will improve efficiency. But, in a free society, the government should never endanger privacy or liberty for efficiency. Besides, when has any government intervention in health care ever improved efficiency or increased patients’ or health care providers’ satisfaction with the system?

The unique patient identifier system puts the desires of government bureaucrats and politically powerful special interests ahead of the needs of individual patients and health care providers. Instead of further intervening in health care and further destroying our privacy and our liberties, Congress should give patients control over their health care by giving them control over health care dollars through expanding access to Health Savings Accounts and health care tax credits. In a free market, patients and doctors can and will work tighter to ensure patients’ records are maintained in a manner that provides maximum efficiency without endangering privacy or liberty.

Apple Watch Saves 30-Year-Old’s Life While Training for a UK Marathon


Apple Watch Series 4 Ecg

A U.K. man who was recently training for a marathon has become the latest person to credit an Apple Watch with helping to save their life.

Phil Harrison, 30, took to Reddit to “say thanks to Apple.” In his original post, Harrison gave an account of how the Apple Watch nudged him to see a doctor while he was training for the Brighton Marathon — and how the wearable may very well have helped save his life.

The 30-year-old said that, although he was aware of some health issues in the past, he thought he was the healthiest he had ever been while he was training.

But, in early April, Harrison said he started getting heart palpitations that didn’t appear to stop. He happened to have an Apple Watch Series 4, which sports a consumer-facing electrocardiogram (ECG) sensor.

When he opened up the ECG app and ran a test, the app sent him a warning that it detected signs of atrial fibrillation and advised him to seek immediate medical attention.

Harrison added that a “series of events” lead him to go to accident and emergency (A&E) services, where he was told that he should not run in the closely approaching marathon. Now, two and a half months later, Harrison said he is about to undergo an open heart valve repair surgery in early July.

While he made sure to thank the doctors and nurses that were integral in his treatment, he added that his Apple Watch ultimately motivated him to seek medical attention.

“But I do know that without my Series 4 watch just giving me a little kick to get to A&E I may not be here today,” Harrison wrote on Reddit. “I would have done everything to run that marathon which most likely would have killed me.”

The ECG feature was first launched on the Apple Watch Series 4, but it was initially only released in the U.S. Since then, Apple has been continually rolling out the feature to new countries. The ECG feature was only available in the UK for a week when Harrison said he used it.

In addition to the Reddit post, Harrison said he also sent an email to Tim Cook and Craig Federighi.

You can view a full list of where the ECG feature is available on Apple’s website.

Researchers reveal lack of evidence for drugs prescribed to treat chronic pain in children


https://m.medicalxpress.com/news/2019-06-reveal-lack-evidence-drugs-chronic.html

Scientists ‘Clear’ Alzheimer’s Plaque From Mice Using Only Light And Sound


Clumps of harmful proteins that interfere with brain functions have been partially cleared in mice using nothing but light and sound.

Research led by MIT has found strobe lights and a low pitched buzz can be used to recreate brain waves lost in the disease, which in turn remove plaque and improve cognitive function in mice engineered to display Alzheimer’s-like behaviour.

main article image

It’s a little like using light and sound to trigger their own brain waves to help fight the disease.

This technique hasn’t been clinically trialled in humans as yet, so it’s too soon to get excited – brain waves are known to work differently in humans and mice.

But, if replicated, these early results hint at a possible cheap and drug-free way to treat the common form of dementia.

So how does it work?

Advancing a previous study that showed flashing light 40 times a second into the eyes of engineered mice treated their version of Alzheimer’s disease, researchers added sound of a similar frequency and found it dramatically improved their results.

“When we combine visual and auditory stimulation for a week, we see the engagement of the prefrontal cortex and a very dramatic reduction of amyloid,” says Li-Huei Tsai, one of the researchers from MIT’s Picower Institute for Learning and Memory.

It’s not the first study to investigate the role sound can play in clearing the brain of the tangles and clumps of tau and amyloid proteins at least partially responsible for the disease.

Previous studies showed bursts of ultrasound make blood vessels leaky enough to allow powerful treatments to slip into the brain, while also encouraging the nervous system’s waste-removal experts, microglia, to pick up the pace.

Several years ago, Tsai discovered light flickering at a frequency of about 40 flashes a second had similar benefits in mice engineered to build up amyloid in their brain’s nerve cells.

“The result was so mind-boggling and so robust, it took a while for the idea to sink in, but we knew we needed to work out a way of trying out the same thing in humans,” Tsai told Helen Thomson at Nature at the time.

The only problem was this effect was confined to visual parts of the brain, missing key areas that contribute to the formation and retrieval of memory.

While the method’s practical applications looked a little limited, the results pointed to a way oscillations could help the brain recover from the grip of Alzheimer’s disease.

As our brain’s neurons transmit signals they also generate electromagnetic waves that help keep remote regions in sync – so-called ‘brain waves’.

One such set of oscillations are defined as gamma-frequencies, rippling across the brain at around 30 to 90 waves per second. These brain waves are most active when we’re paying close attention, searching our memories in order to make sense of what’s going on.

Tsai’s previous study had suggested these gamma waves are impeded in individuals with Alzheimer’s, and might play a pivotal role in the pathology itself.

Light was just one way to trick the parts of the brain into humming in the key of gamma. Sounds can also manage this in other areas.

Instead of the high pitched scream of ultrasound, Tsui used a much lower droning noise of just 40 Hertz, a sound only just high enough for humans to hear.

Exposing their mouse subjects to just one hour of this monotonous buzz every day for a week led to a significant drop in the amount of amyloid build up in the auditory regions, while also stimulating those microglial cells and blood vessels.

“What we have demonstrated here is that we can use a totally different sensory modality to induce gamma oscillations in the brain,” says Tsai.

As an added bonus, it also helped clear the nearby hippocampus – an important section associated with memory.

The effects weren’t just evident in the test subjects’ brain chemistry. Functionally, mice exposed to the treatment performed better in a range of cognitive tasks.

Adding the light therapy from the previous study saw an even more dramatic effect, clearing plaques in a number of areas across the brain, including in the prefrontal cortex. Those trash-clearing microglia also went to town.

“These microglia just pile on top of one another around the plaques,” says Tsai.

Discovering new mechanisms in the way nervous systems clear waste and synchronise activity is a huge step forward in the development of treatments for all kinds of neurological disorders.

Translating discoveries like this to human brains will take more work, especially when there are potential contrasts in how gamma waves appear in mice and human Alzheimer’s brains.

So far early testing for safety has shown the process seems to have no clear side effects.

Are Young Adults Given to More Mental Distress?


Study suggests generational shift in mood disorders, suicide-related outcomes; digital media may play role

Mood disorders increased in young adults across the past decade, with smaller and less consistent trends observed in older adults, according to national survey data.

Of more than 500,000 survey participants, the percentage of adolescents ages 12 to 17 (“iGen,” “Generation Z”) experiencing a major depressive episode in the last year increased by 52% from 2005 to 2017, while the percentage of young adults ages 18 to 25 (“Millennials”) experiencing serious psychological distress in the last month was up 71% from 2008 to 2017, reported Jean Twenge, PhD, of San Diego State University, and colleagues.

The same trends were not observed in respondents ages >25, including “Generation X,” and “Boomers,” with a slight decline in psychological distress observed among adults ≥65. The incidence of major depressive episodes was unchanged, or slightly decreased, in respondents ages ≥26, they wrote in the Journal of Abnormal Psychology.

These trends could be explained by the introduction of smartphones in the developmental stages of more recent generations, Twenge, who is also the author of “iGen,” told MedPage Today.

“When you think of how lives have changes from 2010 to 2017, a clear answer is that over time, people started spending more time on phones and on social media, less time face-to-face with their friends, and less time sleeping,” Twenge said. “As we know from other studies, spending more time with screens, less time sleeping, and less time face-to-face with friends is not a good formula for mental health.”

Depression has increased in the U.S. over recent years, with the fastest rise in youth and young adults, according to health insurance data. Certain aspects of digital media, such as the introduction of smartphones and social media, have also been linked to a higher likelihood of major depressive disorder, specifically among Millennials.

Twenge said youth might be more susceptible to some of the effects of digital media because it was such an integral part of their development early on. She also noted that the findings here contrast with other theories that the increase could be attributed to today’s teens being more open about their mental health, or more willing to seek help, she said, as the current study asked about symptoms and behaviors, instead of inpatient or clinical data regarding specific disorders.

“I think it’s possible the change in social lives of young people has been more pronounced in the age of the smartphone,” Twenge said. “Older people may already have an established social network and the change in how they use their social time may not be as extensive as it has been for teens and young adults.”

“Getting your first smartphone at 12 is fundamentally different than getting your first smartphone at 30,” she added.

Twenge and colleagues used responses from the National Survey on Drug Use and Health of individuals ≥12 years. Rates of serious psychological distress were determined through responses to the Kessler-6 Distress Scale, and rates of major depressive episodes and suicide ideation were determined through NCS-Replication interviews. Deaths by suicide were measured through CDC Fatal Injury Reports (1999-2017).

In total, 212,913 adolescents (ages 12-17) responded from 2005 to 2017 and 398,967 adults (≥18) responded from 2008 to 2017. These groups were similar in terms of sex (51% vs 52% female), race, and ethnicity, with over 50% of both samples being non-Hispanic white, close to 15% being non-Hispanic black, and 15% Hispanic in both groups. A slightly higher percentage of the older group had family incomes <$49,999 compared with the adolescent group (55% vs 46%).

Women had greater increases in mood disorders versus men across the number of reported major depressive episodes, suicide-related outcomes, and serious psychological distress, Twenge and colleagues reported.

The percentage of white Americans experiencing major depressive episodes and suicide-related outcomes increased more than it did for other races or ethnicities, although Hispanic respondents had the greatest increase in psychological stress, they added.

Finally, the biggest increases in psychological distress and suicidal ideation were observed in respondents with the highest family incomes, while increases of adult major depressive disorder and suicide attempts were greater in lower income families.

The authors cautioned against overinterpreting the suicide ideation result, as few respondents reported their thoughts about suicide or attempted suicides. However, they noted that since each later generation had increased thoughts of suicide, it appears this increase was due to cohort as well.

Study limitations included its cross-sectional design and the fact that it included only single-item assessments of suicide ideation or attempts. Suicide-related outcomes also weren’t assessed in adolescents, researchers reported, and irritability was not included in the assessment for this group’s major depressive episodes.

The results suggest a need for more research to understand the role of factors such as technology and digital media use and sleep disturbance may play in mood disorder and suicide-related outcomes, and to develop specialized interventions for younger cohorts, the authors concluded. “This work is necessary given the high cost of mood disorders and suicide.”

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