Tuesday, February 12, 2019

Marvelous and incredible discoveries in Neuroscience.

5 Discoveries That Made 2018 a Huge Year for Neuroscience

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2018 was when neuroscience made the impossible possible.
There was the dazzling array of crazy neurotech: paralyzed patients shopped and texted using an Android tablet with just their brain waves; BrainNet let three people collaboratively play a Tetris-like game using their thoughts; a first memory prosthesis boosted recall in humans; and brain-controlled robotic limbs could know their location in space or even add a “third arm” in able-bodied people.
There was the new lineup of exquisitely detailed brain maps that further unveiled the brain’s nooks and crannies: a digital museum, constructed with the help of a quarter million gamers, that showcases every bend and turn of neurons in the mouse’s retina, or a map in which billions of synapses in the mouse brain light up like the starry night.
It was the year that human brain organoids—“mini-brains” that loosely resemble the real thing during fetal development—grew their own blood supplythrived for months inside mouse brains, and shocked the world by producing electrical patterns that resemble those seen in premature babies, launching a debate on their ethical use.
But that’s not all. Here are five neuroscience findings from 2018 that still blow our minds as we kick off the new year.

1. An infectious side to Alzheimer’s disease

Potential new drugs for Alzheimer’s have all ended up in its notorious graveyard of dreams. Despite best efforts, drugs that target two proteins that build up in Alzheimer’s disease—beta-amyloid and mutant tau—have consistently failed human drug trails.
This year, scientists are beginning to think outside the box, and new theories of how the disease is triggered and progresses are gaining steam.
In October, several studies presented some of the strongest evidence yet that herpes simplex virus type I (HSV1)—the annoying virus responsible for cold sores—may be a potential trigger. Scientists have known since the 1990s that HSV1 confers a large risk for Alzheimer’s in people who carry a specific variant of a gene called APOE4.
Most people get infected with HSV1 as children, and the virus then remains dormant until external cues such as stress reactivate it. The new theory suggests that repeated activation of the virus in adulthood in the brain could cause cumulative damage, particularly in the elderly with declined immune function. If the theory holds water, it means that anti-viral drugs may be a new avenue of treatment.
What’s more, beta-amyloid itself may be transmissible. Using cadaver-derived growth hormones (eww) prepared in the 1980s, a team in Britain injected the sample into mice and found extensive beta-amyloid clumps in their brains. While this doesn’t mean that Alzheimer’s itself is contagious, it does raise concern that medical procedures such as brain surgery could pose a risk for shuttling toxic forms of the protein from one brain to another.

2. Electrical implant restores walking in paralyzed patients

2018 was, without doubt, a breakthrough year for restoring mobility in paralyzed patients.
The technology is several years in the making, with initial positive results in monkeys. It works by implanting a neuroprosthesis into the spinal cord to bypass the site of injury by artificially stimulating remaining nerves.
In September, the Mayo Clinic reported the extraordinary case of Jered Chinnock, who was paralyzed at the waist in 2013. After getting the implant, he walked half the length of a football field. Another report showed that electrical stimulation in four cases was able to help some paralyzed patients go home and get around with only a walker.
Less than a month later, yet another team reported that electrical stimulation using a wireless implant helped three paralyzed patients walk with the aid of crutches or a walker. After a few months of training, the patients could more easily move around even when the stimulation was off, suggesting that the regime had helped remaining healthy nerves rework their connections to adapt and heal.
Electrical stimulation isn’t the only treatment in the works. Another study found that human stem cells, when implanted into monkeys, could synapse with the recipient’s own neurons and restore natural movement after spinal cord injury. These therapies—although expensive and in their infancy—lay a promising road ahead for returning mobility to paralyzed patients.

3. CRISPR barcodes map brain development in exquisite detail

The developing mammalian brain consists of an intricately-choreographed dance of newborn neurons, with each adopting its specific identity and migrating to its home base in the brain. Scientists have long hoped to examine the process in detail, which could help uncover secrets of brain development—and how it goes wrong.
Perhaps unsurprisingly, tracing the history of every single one of the billions of developing cells in the brain has been impossible—until CRISPR came along.
Last August, a team used CRISPR to generate a unique genetic barcode for every single cell in the mouse brain. By reading the barcodes, scientists were able to retrace a cell’s entire history in the developing brain. Like genetic sleuths, the scientists reconstructed entire cellular family trees to show how cells relate to one another.
It’s a technical tour-de-force, and a “holy grail” for developmental biology, earning Science’s Breakthrough of the Year title. The trove of technologies and data are poised to uncover how human cells mature with age, how tissues regenerate, and how the processes go wrong in disease.

4. A new type of neuron in the cortex that’s potentially uniquely human

Perhaps shockingly, even today neuroscientists are still uncovering new cellular components that make up our mighty brains. Last year saw the discovery of giant neurons within the claustrum, a thin sheet of cells that some believe is the seat of consciousness.
This year, the Allen Institute in Seattle is back at it with another finding: rosehip neurons, each containing dense bundles of processes around the cell’s center that make it look like a rose after shedding its petals.
These neurons make up nearly 15 percent of neurons in the outermost layer of the brain that supports high-level cognitive functions. Remarkably, rosehip neurons have never before been seen in mice or other well-studied lab animals. Although the team can’t yet fully conclude that they’re specific to humans, their scarcity within the animal kingdom is intriguing.
The next step is figuring out the functions of these rose-like neurons—in particular, are they partly why our brains are special?—and whether they are linked to neuropsychiatric disorders.

5. Gut-brain connection grows stronger with direct anatomical link

One of the hottest research trends in neuroscience is the link between the brain and the gut—often dubbed the “little brain.”
The human gut is lined with over 100 million nerve cells that allow it to talk to the brain, letting us know when we’re hungry or when we’ve over-indulged. But it’s not all digestion: scientists are increasingly realizing that the gut could contribute to anxiety, depression, or more controversially, cognition.
Last year scientists found a new set of informational highways that directly link the gut to the brain. Within the gut, enteroendocrine cells pump out hormones that kick off digestion and suppress hunger. These cells have little foot-like protrusions that look remarkably like synapses—the structure that neurons use to talk to each other using chemicals.
With the help of a glow-in-the-dark rabies virus, which can jump from synapse to synapse, the team found that enteroendocrine cells directly link to neurons in the vagus nerve—a giant nerve that runs from the brain to vital organs such as the heart and lungs. What’s more, they chat with their partners using classical neurotransmitters including glutamate and serotonin, which work much faster than hormones.
Another study found that the gut directly links to the brain’s reward centers through the vagus nerve. Using lasers to zap sensory neurons in the gut of mice, the scientists found increased levels of mood-boosting dopamine in their brains.
These new connections could explain why vagus nerve stimulation is potentially helpful for those with severe depression. More relevant to the holiday season, it also could explain why eating makes us feel warm and fuzzy.
Uncovering the gut-brain connection is gaining steam as a research field. Eventually, the findings could lead to new treatments for disorders linked to a malfunctioning gut—for example, obesity, eating disorders, depression, or even autism.
Image Credit: wowow / Shutterstock.com
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Shelly Xuelai Fan is a neuroscientist at the University of California, San Francisco, where she studies ways to make old brains young again. In addition to research, she's also an avid science writer with an insatiable obsession with biotech, AI and all things neuro. She spends her spare time kayaking, bike camping and getting lost in the woods.

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Monday, February 11, 2019

China and India are winning the Green revolution!

NASA Ames
Feb. 11, 2019

Human Activity in China and India Dominates the Greening of Earth, NASA Study Shows

A map showing increases in leaf area per year, represented in green. India and China stand out with large areas of dark green.
Over the last two decades, the Earth has seen an increase in foliage around the planet, measured in average leaf area per year on plants and trees. Data from NASA satellites shows that China and India are leading the increase in greening on land. The effect stems mainly from ambitious tree planting programs in China and intensive agriculture in both countries.
Credits: NASA Earth Observatory
The world is literally a greener place than it was 20 years ago, and data from NASA satellites has revealed a counterintuitive source for much of this new foliage: China and India. A new study shows that the two emerging countries with the world’s biggest populations are leading the increase in greening on land. The effect stems mainly from ambitious tree planting programs in China and intensive agriculture in both countries.
The greening phenomenon was first detected using satellite data in the mid-1990s by Ranga Myneni of Boston University and colleagues, but they did not know whether human activity was one of its chief, direct causes. This new insight was made possible by a nearly 20-year-long data record from a NASA instrument orbiting the Earth on two satellites. It’s called the Moderate Resolution Imaging Spectroradiometer, or MODIS, and its high-resolution data provides very accurate information, helping researchers work out details of what’s happening with Earth’s vegetation, down to the level of 500 meters, or about 1,600 feet, on the ground.
A world map showing the trend in annual average leaf area, in percent per decade (2000-2017)
The world is a greener place than it was 20 years ago, as shown on this map, where areas with the greatest increase in foliage are indicated in dark green. Data from a NASA instrument orbiting Earth aboard two satellites show that human activity in China and India dominate this greening of the planet.
Credits: NASA Earth Observatory
Taken all together, the greening of the planet over the last two decades represents an increase in leaf area on plants and trees equivalent to the area covered by all the Amazon rainforests. There are now more than two million square miles of extra green leaf area per year, compared to the early 2000s – a 5% increase.
“China and India account for one-third of the greening, but contain only 9% of the planet’s land area covered in vegetation – a surprising finding, considering the general notion of land degradation in populous countries from overexploitation,” said Chi Chen of the Department of Earth and Environment at Boston University, in Massachusetts, and lead author of the study.
An advantage of the MODIS satellite sensor is the intensive coverage it provides, both in space and time: MODIS has captured as many as four shots of every place on Earth, every day for the last 20 years.
“This long-term data lets us dig deeper,” said Rama Nemani, a research scientist at NASA’s Ames Research Center, in California’s Silicon Valley, and a co-author of the new work. “When the greening of the Earth was first observed, we thought it was due to a warmer, wetter climate and fertilization from the added carbon dioxide in the atmosphere, leading to more leaf growth in northern forests, for instance. Now, with the MODIS data that lets us understand the phenomenon at really small scales, we see that humans are also contributing.”
China’s outsized contribution to the global greening trend comes in large part (42%) from programs to conserve and expand forests. These were developed in an effort to reduce the effects of soil erosion, air pollution and climate change. Another 32% there – and 82% of the greening seen in India – comes from intensive cultivation of food crops.
Land area used to grow crops is comparable in China and India – more than 770,000 square miles – and has not changed much since the early 2000s. Yet these regions have greatly increased both their annual total green leaf area and their food production. This was achieved through multiple cropping practices, where a field is replanted to produce another harvest several times a year. Production of grains, vegetables, fruits and more have increased by about 35-40% since 2000 to feed their large populations.
How the greening trend may change in the future depends on numerous factors, both on a global scale and the local human level. For example, increased food production in India is facilitated by groundwater irrigation. If the groundwater is depleted, this trend may change.
“But, now that we know direct human influence is a key driver of the greening Earth, we need to factor this into our climate models,” Nemani said. “This will help scientists make better predictions about the behavior of different Earth systems, which will help countries make better decisions about how and when to take action.”
The researchers point out that the gain in greenness seen around the world and dominated by India and China does not offset the damage from loss of natural vegetation in tropical regions, such as Brazil and Indonesia. The consequences for sustainability and biodiversity in those ecosystems remain.
Overall, Nemani sees a positive message in the new findings. “Once people realize there’s a problem, they tend to fix it,” he said. “In the 70s and 80s in India and China, the situation around vegetation loss wasn’t good; in the 90s, people realized it; and today things have improved. Humans are incredibly resilient. That’s what we see in the satellite data.”
This research was published online, Feb. 11, 2019, in the journal Nature Sustainability.
 
Bar chart showing that China and India are leading the increase in greening of the planet, due to human activity
Credits: NASA Earth Observatory
For news media:
Members of the news media interested in covering this topic should get in touch with the science representative on the NASA Ames media contacts page.
Author: Abby Tabor, NASA's Ames Research Center, Silicon Valley
Last Updated: Feb. 11, 2019
Editor: Abigail Tabor

Can A.I. diagnose a disease faster than humans?

Longevity & Vitality Part 3: AI Augments Healthcare and Longevity

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Feb 10, 2019, 1:17 PM (1 day ago)
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When it comes to the future of healthcare, perhaps the only technology more powerful than CRISPR is Artificial Intelligence.
Over the past five years, healthcare AI startups around the globe raised over $4.3 billion across 576 deals, topping all other industries in AI deal activity.
During this same period, the FDA has given 70 AI healthcare tools and devices ‘fast-tracked approval’ because of their ability to save both lives and money.
The pace of AI-augmented healthcare innovation is only accelerating.
In Part 3 of this blog series on Longevity & Vitality, I cover the different ways in which AI is augmenting our healthcare system, enabling us to live longer and healthier lives.
In this blog, I’ll expand on:
  1. Machine learning and drug design
  2. Artificial Intelligence and Big Data in medicine
  3. Healthcare, AI & China
Let’s dive in.

Machine Learning in Drug Design

What if AI systems, specifically neural networks, could predict the design of novel molecules (i.e. medicines) capable of targeting and curing any disease?
Imagine leveraging cutting-edge artificial intelligence to accomplish with 50 people what the pharmaceutical industry can barely do with an army of 5,000.
And what if these molecules, accurately engineered by AIs, always worked? Such a feat would revolutionize our $1.3 trillion global pharmaceutical industry, which currently holds a dismal record of 1 in 10 target drugs ever reaching human trials.
It’s no wonder that drug development is massively expensive and slow. It takes over 10 years to bring a new drug to market, with costs ranging from $2.5 billion to $12 billion.
This inefficient, slow-to-innovate, and risk-averse industry is a sitting duck for disruption in the years ahead. 
One of the hottest startups in digital drug discovery today is Insilico Medicine.
Leveraging AI in its end-to-end drug discovery pipeline, Insilico Medicine aims to extend healthy longevity through drug discovery and aging research. 
Their comprehensive drug discovery engine uses millions of samples and multiple data types to discover signatures of disease, identify the most promising protein targets, and generate perfect molecules for these targets. 
These molecules either already exist or can be generated de novo with the desired set of parameters.
In late 2018, Insilico’s CEO Dr. Alex Zhavoronkov announced the groundbreaking result of generating novel molecules for a challenging protein target with an unprecedented hit rate in under 46 days. This included both synthesis of the molecules and experimental validation in a biological test system — an impressive feat made possible by converging exponential technologies.
Underpinning Insilico’s drug discovery pipeline is a novel machine learning technique called Generative Adversarial Networks (GANs), used in combination with deep reinforcement learning. 
Generating novel molecular structures for diseases both with and without known targets, Insilico is now pursuing drug discovery in aging, cancer, fibrosis, Parkinson’s disease, Alzheimer’s disease, ALS, diabetes, and many others. Once rolled out, the implications will be profound. 
Dr. Zhavoronkov’s ultimate goal is to develop a fully automated Health-as-a-Service (HaaS) and Longevity-as-a-Service (LaaS) engine.
Once plugged into the services of companies from Alibaba to Alphabet, such an engine would enable personalized solutions for online users, helping them prevent diseases and maintain optimal health.
Insilico, alongside other companies tackling AI-powered drug discovery, truly represents the application of the 6 D’s. What was once a prohibitively expensive and human-intensive process is now rapidly becoming digitized, dematerialized, demonetized and, perhaps most importantly, democratized. 
Companies like Insilico can now do with a fraction of the cost and personnel what the pharmaceutical industry can barely accomplish with thousands of employees and a hefty bill to foot.
As I discussed in my blog on ‘The Next Hundred-Billion-Dollar Opportunity,’ Google’s DeepMind has now turned its neural networks to healthcare, entering the digitized drug discovery arena.
In 2017, DeepMind achieved a phenomenal feat by matching the fidelity of medical experts in correctly diagnosing over 50 eye disorders.
And just a year later, DeepMind announced a new deep learning tool called AlphaFold. By predicting the elusive ways in which various proteins fold on the basis of their amino acid sequences, AlphaFold may soon have a tremendous impact in aiding drug discovery and fighting some of today’s most intractable diseases. 

Artificial Intelligence and Data Crunching

AI is especially powerful in analyzing massive quantities of data to uncover patterns and insights that can save lives. 
Take WAVE, for instance.
Every year, over 400,000 patients die prematurely in U.S. hospitals as a result of heart attack or respiratory failure. 
Yet these patients don’t die without leaving plenty of clues. Given information overload, however, human physicians and nurses alone have no way of processing and analyzing all necessary data in time to save these patients’ lives.
Enter WAVE, an algorithm that can process enough data to offer a six-hour early warning of patient deterioration. 
Just last year, the FDA approved WAVE as an AI-based predictive patient surveillance system to predict and thereby prevent sudden death.
Another highly valuable yet difficult-to-parse mountain of medical data comprises the 2.5 million medical papers published each year. 
For some time, it has become physically impossible for a human physician to read — let alone remember — all of the relevant published data.
To counter this compounding conundrum, Johnson & Johnson is teaching IBM Watson to read and understand scientific papers that detail clinical trial outcomes. 
Enriching Watson’s data sources, Apple is also partnering with IBM to provide access to health data from mobile apps. 
One such Watson system contains 40 million documents, ingesting an average of 27,000 new documents per day, and providing insights for thousands of users.
After only one year, Watson’s successful diagnosis rate of lung cancer has reached 90 percent, compared to the 50 percent success rate of human doctors. 
But what about the vast amount of unstructured medical patient data that populates today's ancient medical system? This includes medical notes, prescriptions, audio interview transcripts, pathology and radiology reports.
In late 2018, Amazon announced a new HIPAA-eligible machine learning service that digests and parses unstructured data into categories, such as patient diagnosis, treatments, dosages, symptoms and signs. 
Taha Kass-Hout, Amazon’s senior leader in health care and artificial intelligence, told the WSJ that internal tests demonstrated that the software even performs as well as or better than other published efforts.
On the heels of this announcement, Amazon confirmed it was teaming up with the Fred Hutchinson Cancer Research Center to evaluate "millions of clinical notes to extract and index medical conditions.” 
Having already driven extraordinary algorithmic success rates in other fields, data is the healthcare industry’s goldmine for future innovation. 

Healthcare, AI & China 

In 2017, the Chinese government published its ambitious national plan to become a global leader in AI research by 2030, with healthcare listed as one of four core research areas during the first wave of the plan. 
Just a year earlier, China began centralizing healthcare data, tackling a major roadblock to developing longevity and healthcare technologies (particularly AI systems): scattered, dispersed, and unlabeled patient data.
Backed by the Chinese government, China’s largest tech companies — particularly Tencent — have now made strong entrances into healthcare.
Just recently, Tencent participated in a $154 million megaround for China-based healthcare AI unicorn iCarbonX.
Hoping to develop a complete digital representation of your biological self, iCarbonX has acquired numerous U.S. personalized medicine startups.
Considering Tencent’s own Miying healthcare AI platform — aimed at assisting healthcare institutions in AI-driven cancer diagnostics — Tencent is quickly expanding into the drug discovery space, participating in two multimillion-dollar, U.S.-based AI drug discovery deals just this year.
China’s biggest, second-order move into the healthtech space comes through Tencent’s WeChat. In the course of a mere few years, already 60 percent of the 38,000 medical institutions registered on WeChat allow patients to digitally book appointments through Tencent’s mobile platform. 
At the same time, 2,000 Chinese hospitals accept WeChat payments.
Tencent has additionally partnered with the U.K.’s Babylon Health, a virtual healthcare assistant startup whose app now allows Chinese WeChat users to message their symptoms and receive immediate medical feedback.
Similarly, Alibaba’s healthtech focus started in 2016 when it released its cloud-based AI medical platform, ET Medical Brain, to augment healthcare processes through everything from diagnostics to intelligent scheduling.

Conclusion

As Nvidia CEO Jensen Huang has stated, “Software ate the world, but AI is going to eat software.” Extrapolating this statement to a more immediate implication, AI will first eat healthcare, resulting in dramatic acceleration of longevity research and an amplification of the human healthspan.
Next week, I’ll continue to explore this concept of AI systems in healthcare.
Particularly, I’ll expand on how we’re acquiring and using the data for these doctor-augmenting AI systems: from ubiquitous biosensors, to the mobile healthcare revolution, and finally, to the transformative power of the health nucleus.
As AI and other exponential technologies increase our healthspan by 30 to 40 years, how will you leverage these same exponential technologies to take on your Moonshots and live out your Massively Transformative Purpose?

Join Me

(1) A360 Executive Mastermind: This is one of the key conversations I’ll be exploring at my Executive Mastermind group called Abundance 360. The program is highly selective, for 360 abundance- and exponentially minded CEOs (running $10M to $50B companies). If you’d like to be considered, apply here.
Share this with your friends, especially if they are interested in any of the areas outlined above.
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