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Genes from scratch: Far more common and important than we thought


Trinity College Dublin
Mon, 17 Feb 2020 09:49 UTC
genes adn dna
© Foto ilustrativa / Pixbay.com
Scientists from Trinity and the University of Pittsburgh have discovered that de novo genes - genes that have evolved from scratch - are both more common and more important than previously believed.

Their findings appear in two studies, one which will appear in eLIFE tomorrow and one which was published earlier this month in Nature Communications.

DNA, genes, and de novo orphans

Over time, genes change via random mutations. Some of these changes result in serious defects and are rarely passed on to the next generations, others have little impact, and others confer significant advantages, which become favoured due to natural selection and end up being passed on to future generations.

This is the main source of genetic novelty and how organisms differ from each other. However, genetic novelty can also be generated by totally new genes evolving from scratch.

Comment: See also: Can Nature create new genes from scratch?

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Microscope 1

40 Trillion cells in your body and each poses a mystery! Part II of "Secrets of the Cell with Michael Behe"

David Klinghoffer
Evolution News
Wed, 19 Feb 2020 17:33 UTC
Michael Behe

Michael Behe
"Except for guys like these, not everyone really understands what's inside." So says Lehigh University biochemist Michael Behe on a second episode of Secrets of the Cell, the new and beautifully produced video series that launched last week. See it below. He's referring to a group of expert auto mechanics at their work. And Professor Behe is right: I'm sorry to say that I'm among that majority of us, 54 percent of Americans according to a poll reported by Fox News, who "feel intimidated when dealing with a car mechanic."


Comment: The first episode: Darwin Day: Discovery Institute's Video series "Secrets of the Cell with Michael Behe"

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Arrow Up

Alibaba research institute develops AI-powered algorithm that identifies coronavirus infections with 96% accuracy

Sun Henan
KrAsia
Mon, 17 Feb 2020 00:00 UTC
The system can complete the recognition process within 20 seconds.
AI powered diagnosis system
A new AI-powered diagnosis system promises to detect new coronavirus cases with an accuracy rate of up to 96% via computerized tomography (CT) scans, local tech outlet Sina Tech News reported on Saturday.

The diagnosis algorithm was developed by Alibaba's research institute Damo Academy. Researchers at the academy said they have trained the AI model with sample data from more than 5,000 confirmed cases, adding that the system can identify differences in CT scans between patients infected with the novel virus and those with ordinary viral pneumonia with an accuracy of up to 96%. The algorithm includes the latest treatment guidelines and recently published research, said its creators.

The new diagnostic tool was first introduced in Qiboshan Hospital in Zhengzhou, Henan province, which was modeled after the Beijing Xiaotangshan Hospital, completed in 2003 for the SARS crisis. The hospital has already started accepting patients infected with coronavirus on Sunday.

The system will also be adopted in more than 100 hospitals in the provinces of Hubei, Guangdong, and Anhui, said Alibaba.

Comment: Hey, China-bashers! Maybe China deserves PRAISE for the way it's handling the Coronavirus outbreak?

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Monkey Wrench

Hackers can trick a Tesla car into accelerating by 50 miles per hour

Patrick Howell O'Neill
MIT Technology Review
Wed, 19 Feb 2020 00:00 UTC
Tesla car
© Tesla
A two inch piece of tape fooled the Tesla's cameras and made the car quickly and mistakenly speed up.

Don't believe your car's lying eyes.

Hackers have manipulated multiple Tesla cars into speeding up by 50 miles per hour. The researchers fooled the car's Mobileye EyeQ3 camera system by subtly altering a speed limit sign on the side of a road in a way that a person driving by would almost never notice.

This demonstration from the cybersecurity firm McAfee is the latest indication that adversarial machine learning can potentially wreck autonomous driving systems, presenting a security challenge to those hoping to commercialize the technology.

Mobileye EyeQ3 camera systems read speed limit signs and feed that information into autonomous driving features like Tesla's automatic cruise control, said Steve Povolny and Shivangee Trivedi from McAfee's Advanced Threat Research team.

The researchers stuck a tiny and nearly imperceptible sticker on a speed limit sign. The camera read the sign as 85 instead of 35, and in testing, both the 2016 Tesla Model X and that year's Model S sped up 50 miles per hour.
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Cassiopaea

The plasma universe and Max Planck's musical space-time revisited

Matthew Ehret
Rising Tide Foundation
Wed, 19 Feb 2020 21:51 UTC
planck
© Rising Tide Foundation
Near the end of 2019, signals arrived to Earth from the Voyager 2 spacecraft which have shaken the foundations of modern physics, and brought into question what are the forces and principles shaping the space time of stars within galaxies (and implicitly galaxies within clusters of galaxies). The data which NASA scientists received from Voyager 2 have catapulted mankind's ability to finally answer the old question of "what is in the "space" between stars or even between galaxies within our universe? As Voyager Project scientist Ed Stone stated:

"The Voyager probes are showing us how our sun interacts with the stuff that fills most of the space between stars in the milky way Galaxy."

What did Voyager 2 encounter?

As Voyager 2 exited the Heliosphere (the spherical boundary shaped by the sun's electro-magnetic field) and moved into the interstellar medium on November 5, 2019, the five sensors still functioning on the craft which was launched in 1977 alongside Voyager-1, measuring magnetic field intensity, cosmic radiation flux and plasma density produced surprising results. As the magnetic field intensity from the sun was no longer felt, an ocean of extremely dense cosmic radiation and plasma was encountered. Voyager-2's results corroborate those same measurements which occurred on the faster moving Voyager-1 when it traversed the Heliosphere in 2012 proving that this was not a "localized phenomenon".

Comment: See also: Also check out SOTT radio's:

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Rocket

More efficient rocket engines developed by scientist

Sarah MCQuate
University of Washington News
Tue, 18 Feb 2020 20:03 UTC
Soyuz spacecraft launches
© NASA/Bill Ingalls/Flickr
A Soyuz spacecraft launches from the Baikonur Cosmodrome in Kazakhstan in 2017 using a conventional, fuel-intensive engine. UW researchers have developed a mathematical model that describes how a new type of engine — one that promises to make rockets fuel-efficient, more lightweight and less complicated to construct — works.
It takes a lot of fuel to launch something into space. Sending NASA's Space Shuttle into orbit required more than 3.5 million pounds of fuel, which is about 15 times heavier than a blue whale.

But a new type of engine — called a rotating detonation engine — promises to make rockets not only more fuel-efficient but also more lightweight and less complicated to construct. There's just one problem: Right now this engine is too unpredictable to be used in an actual rocket.

Researchers at the University of Washington have developed a mathematical model that describes how these engines work. With this information, engineers can, for the first time, develop tests to improve these engines and make them more stable. The team published these findings Jan. 10 in Physical Review E.

"The rotating detonation engine field is still in its infancy. We have tons of data about these engines, but we don't understand what is going on," said lead author James Koch, a UW doctoral student in aeronautics and astronautics. "I tried to recast our results by looking at pattern formations instead of asking an engineering question — such as how to get the highest performing engine — and then boom, it turned out that it works."

A conventional rocket engine works by burning propellant and then pushing it out of the back of the engine to create thrust.
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Blue Pill

Darwinist Jerry Coyne jumps into the Dawkins eugenics fray


Uncommon Descent
Tue, 18 Feb 2020 19:07 UTC
jerry coyne
© YouTube
Jerry Coyne on The Dave Rubin Show
Almost like he must:
Artificial selection will work if a trait has any positive heritability, that is, if any proportion of the total variation in a trait among individuals in a population is due to genetic variation — what we specifically call "additive genetic variance" in the trade. And virtually all morphological or behavioral traits have some positive heritability.

Look at domestic dog breeds, for instance. All of them descend from the wolf, yet all the huge variety of their traits: the variation in their size, their shape, their color, and even their behavior (retrievers, border collies, etc.) have come from selecting on traits that have a positive heritability. As Darwin said in The Origin, "Breeders habitually speak of an animal's organization as something quite plastic, which they can model almost as they please."

That happens to be true. And it would be true of humans as well if we were able to select on them.

Jerry Coyne, "Dawkins makes a tweet" at Why Evolution Is True
Actually, eugenics wouldn't work in humans because reason and personal choice can frustrate efforts at programming.


Comment: Not to mention the fact that great people can be born to monsters, and vice versa.


Another issue was raised by a reader who reminds us that, in any event, dog breeding is devolution for dogs. It usually works that way, as Michael Behe points out in Darwin Devolves. Dogs are bred by humans at the expense of their genetic health. Some call it "malgenics."

That's quite correct. Domestic dog breeds often have serious inbred problems that the feral cur never knew. He stays alive despite all those who want to kill him. The pampered pedigreed with the fashionable but costly features might expire despite the vet's best efforts to save him. - News

Comment: It's things like this that show why you shouldn't automatically trust experts. They're often experts at being idiots. But their 'expertise' goes to their heads, inflating their self-importance, and the conviction that they actually know what they're doing. It's people like Dawkins and Coyne who rationally explain why things "should" or "will" work, when the actual implementation of their plans and policies results in disaster because they were either completely wrong to begin with, or were unaware of hidden variables. Don't trust experts to come up with solutions that don't already have a good track record.

Geneticist Dave Curtis has a useful Twitter thread on why eugenics just wouldn't work on humans.

See also:

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X

If human eugenics wouldn't work, human evolution has a big problem

David Klinghoffer
Evolution News
Tue, 18 Feb 2020 23:05 UTC
dawkings
Richard Dawkins got his wings clipped over the weekend, following a claim on Twitter that human eugenics, whatever its demerits otherwise, would certainly work. After all, it does with animals: "It works for cows, horses, pigs, dogs & roses. Why on earth wouldn't it work for humans?"


He was quickly forced to backpedal a bit, "For those determined to miss the point," saying he "deplores" it as a policy, "I simply said deploring it doesn't mean it wouldn't work." And again, "A eugenic policy would be bad. I'm combating the illogical step from 'X would be bad' to 'So X is impossible'."

Comment: See also:

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Pi

Dynamic system of feedback loops: A mathematical model unlocks the secrets of vision

Kevin Hartnett
Quanta Magazine
Wed, 21 Aug 2019 00:00 UTC
The first anatomically correct model of the visual cortex seeks to capture how the brain sees the world.
eye system image replication
© DVDP FOR QUANTA MAGAZINE
Information from the eye passes through a bottleneck before it gets to the brain’s visual cortex, which heavily processes the sparse signal.
Mathematicians and neuroscientists have created the first anatomically accurate model that explains how vision is possible. Information from the eye passes through a bottleneck before it gets to the brain's visual cortex, which heavily processes the sparse signal.

This is the great mystery of human vision: Vivid pictures of the world appear before our mind's eye, yet the brain's visual system receives very little information from the world itself. Much of what we "see" we conjure in our heads.

"A lot of the things you think you see you're actually making up," said Lai-Sang Young, a mathematician at New York University. "You don't actually see them."
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Info

Unknown layer of information discovered in RNA

Ingrid Spilde
Science Nordic
Mon, 17 Feb 2020 10:43 UTC
RNA Has New Layer
© Illustration: nobeastsofierce / Shutterstock / NTB scanpix
RNA has become a hot topic, particularly in cancer research.
And we've only just gotten used to epigenetics!

Just a few years ago, scientists began to realize that our genes, neatly written with chemical letters in our DNA, are actually not carved in stone.

Although genes themselves don't change, they can be regulated.

They are turned on and off as we grow and develop. These changes are influenced by our surroundings, so we actually change over the course of our lives. And some of these changes in regulation are passed on to our children.

Figuratively speaking, our DNA can be described as the recipe book for who and how we are, while epigenetic regulation can be seen as notes that have been pencilled into the margin.

Epigenetics thus describes a fascinating layer of information and regulation of our genes that enables us to adapt to new environments much faster than via normal evolution.

But lately, scientists have seen evidence of something more.

Another layer.

This time it's not about DNA, but about RNA, says Professor Arne Klungland at the University of Oslo.

"There has been an extreme interest in this field over the last five years," says Klungland, who himself leads one of the few research groups in the world that has worked in the field for a long time.
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