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What Will Eat You?

QuestionWhat is a “food web?” 

Joel Cohen: A food web is a description of which species living in a place eat which other species. You can think of it like a roadmap with one-way streets. It shows you, if there's an arrow from A to B, it means the energy flows from A to B, or in other words, B eats A, okay? So it's usually drawn with a bunch of circles, you put the name of a species in the circle and then you draw an arrow showing which way the food is flowing. Okay? That's what a food web is. 

Now, we have just been talking about a food web. We've been talking about the food web in which people eat ducks, geese, swine, cattle, okay? And, what most people don't realize is, the things that eat us are the infectious diseases, like the viruses and the bacteria and the worms and the other parasites, much more important than the lions and the tigers. 

And what I've been studying is how the animals we eat put us at risk of being eaten by the infectious agents that eat those animals. So when we eat the duck, it puts us at risk of being eaten by the virus that eats the duck, the H5N1. But let me give you some other examples, okay? The monkeys that live in the forests of west Africa, have long been infected by a virus called the simian influenza—sorry, simian immunodeficiency virus. Okay? SIV. We now believe that people went hunting for those monkeys and either got the blood in their hands or ate them without cooking them fully, and the simian immunodeficiency virus infected the people who were dealing with the blood from those animals and evolved very slightly, because we can compare the genes, and gave us the human immunodeficiency virus, HIV. So by going into a new habitat, eating the monkeys and getting their blood, the things that were eating the monkeys turned to eating us. That's the current understanding of the origin of HIV. It was going after food in the forest. 

Another, okay, do you follow that? We've talked about avian influenza, that's from the expansion into new habitats. Another example is swine flu and trichinosis. We eat the pigs, the worms of trichinosis, if they're not cooked to death and we eat uncooked ham or pork, they start infecting the people. The influenza that swine have infects the people who live with the swine. A last example, mad cow disease. Mad cow disease is a prion that causes bovine spongiform encephalitis, BES. If you eat the flesh of a cow that has been eaten by one of those prions, it will eat you, and then you get Jackob Creutzfeldt disease. 

And, so there's a World Health Organization for animals, did you know that? Probably not.  It's World Organization for Animal Health, it's called, and they have a long list of what are called zoonotic diseases. And a zoonotic disease is a disease that regularly infects vertebrates and will also infect people if they are exposed to it. And many, many, many of those zoonotic diseases are diseases that arise because we raise domestic animals for meat. So there's a connection with the meat and our health that's very close. 

Humans exist in a "food web," wherein we enjoy our familiar menu of plants, vegetables, animals and their by-products, etc; but what’s out there itching to get ahold of us…and how can we stop it?

Does conscious AI deserve rights?

If machines develop consciousness, or if we manage to give it to them, the human-robot dynamic will forever be different.

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  • Does AI—and, more specifically, conscious AI—deserve moral rights? In this thought exploration, evolutionary biologist Richard Dawkins, ethics and tech professor Joanna Bryson, philosopher and cognitive scientist Susan Schneider, physicist Max Tegmark, philosopher Peter Singer, and bioethicist Glenn Cohen all weigh in on the question of AI rights.
  • Given the grave tragedy of slavery throughout human history, philosophers and technologists must answer this question ahead of technological development to avoid humanity creating a slave class of conscious beings.
  • One potential safeguard against that? Regulation. Once we define the context in which AI requires rights, the simplest solution may be to not build that thing.

A new hydrogel might be strong enough for knee replacements

Duke University researchers might have solved a half-century old problem.

Photo by Alexander Hassenstein/Getty Images
Technology & Innovation
  • Duke University researchers created a hydrogel that appears to be as strong and flexible as human cartilage.
  • The blend of three polymers provides enough flexibility and durability to mimic the knee.
  • The next step is to test this hydrogel in sheep; human use can take at least three years.
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Hints of the 4th dimension have been detected by physicists

What would it be like to experience the 4th dimension?

Two different experiments show hints of a 4th spatial dimension. Credit: Zilberberg Group / ETH Zürich
Technology & Innovation

Physicists have understood at least theoretically, that there may be higher dimensions, besides our normal three. The first clue came in 1905 when Einstein developed his theory of special relativity. Of course, by dimensions we’re talking about length, width, and height. Generally speaking, when we talk about a fourth dimension, it’s considered space-time. But here, physicists mean a spatial dimension beyond the normal three, not a parallel universe, as such dimensions are mistaken for in popular sci-fi shows.

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Predicting PTSD symptoms becomes possible with a new test

An algorithm may allow doctors to assess PTSD candidates for early intervention after traumatic ER visits.

Image source: camillo jimenez/Unsplash
Technology & Innovation
  • 10-15% of people visiting emergency rooms eventually develop symptoms of long-lasting PTSD.
  • Early treatment is available but there's been no way to tell who needs it.
  • Using clinical data already being collected, machine learning can identify who's at risk.

The psychological scars a traumatic experience can leave behind may have a more profound effect on a person than the original traumatic experience. Long after an acute emergency is resolved, victims of post-traumatic stress disorder (PTSD) continue to suffer its consequences.

In the U.S. some 30 million patients are annually treated in emergency departments (EDs) for a range of traumatic injuries. Add to that urgent admissions to the ED with the onset of COVID-19 symptoms. Health experts predict that some 10 percent to 15 percent of these people will develop long-lasting PTSD within a year of the initial incident. While there are interventions that can help individuals avoid PTSD, there's been no reliable way to identify those most likely to need it.

That may now have changed. A multi-disciplinary team of researchers has developed a method for predicting who is most likely to develop PTSD after a traumatic emergency-room experience. Their study is published in the journal Nature Medicine.

70 data points and machine learning

nurse wrapping patient's arm

Image source: Creators Collective/Unsplash

Study lead author Katharina Schultebraucks of Columbia University's Department Vagelos College of Physicians and Surgeons says:

"For many trauma patients, the ED visit is often their sole contact with the health care system. The time immediately after a traumatic injury is a critical window for identifying people at risk for PTSD and arranging appropriate follow-up treatment. The earlier we can treat those at risk, the better the likely outcomes."

The new PTSD test uses machine learning and 70 clinical data points plus a clinical stress-level assessment to develop a PTSD score for an individual that identifies their risk of acquiring the condition.

Among the 70 data points are stress hormone levels, inflammatory signals, high blood pressure, and an anxiety-level assessment. Says Schultebraucks, "We selected measures that are routinely collected in the ED and logged in the electronic medical record, plus answers to a few short questions about the psychological stress response. The idea was to create a tool that would be universally available and would add little burden to ED personnel."

Researchers used data from adult trauma survivors in Atlanta, Georgia (377 individuals) and New York City (221 individuals) to test their system.

Of this cohort, 90 percent of those predicted to be at high risk developed long-lasting PTSD symptoms within a year of the initial traumatic event — just 5 percent of people who never developed PTSD symptoms had been erroneously identified as being at risk.

On the other side of the coin, 29 percent of individuals were 'false negatives," tagged by the algorithm as not being at risk of PTSD, but then developing symptoms.

Going forward

person leaning their head on another's shoulder

Image source: Külli Kittus/Unsplash

Schultebraucks looks forward to more testing as the researchers continue to refine their algorithm and to instill confidence in the approach among ED clinicians: "Because previous models for predicting PTSD risk have not been validated in independent samples like our model, they haven't been adopted in clinical practice." She expects that, "Testing and validation of our model in larger samples will be necessary for the algorithm to be ready-to-use in the general population."

"Currently only 7% of level-1 trauma centers routinely screen for PTSD," notes Schultebraucks. "We hope that the algorithm will provide ED clinicians with a rapid, automatic readout that they could use for discharge planning and the prevention of PTSD." She envisions the algorithm being implemented in the future as a feature of electronic medical records.

The researchers also plan to test their algorithm at predicting PTSD in people whose traumatic experiences come in the form of health events such as heart attacks and strokes, as opposed to visits to the emergency department.

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