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The Next Nutty Science Idea

Question: How much longer will the universe exist? 

Robert Kirshner: Yeah. The time scale – the age of the universe now, we think is about 14 billion years. So, the universe has been expanding from this hot dense state in all directions, the Big Bang. And it’s been elaborated over time. Gravity has made things clump together so galaxies have formed, stars have formed, stars go through their lifecycle and they emit as they blow up as supernovae and put out heavy elements that are used by the next generation of stars and then they put planets. You have in your bones calcium atoms that were manufactured in supernovae, iron that’s in our blood, air that you’re breathing. Those nuclei, those actual atoms came from stars that blew up before the sun formed. So, you’re really part of this whole story, part of the universe. So that’s the story that we know has been going on in the past.

The piece in the future is much, much harder for us to say with confidence because after all, we always – there’s always that big voice that – astronomers know, the universe began in a powerful explosion 14 billion years ago. And that’s the voice in the planetarium and that’s the voice of authority. And it’s the voice of conventional wisdom. And we always talk like that. The trouble is, its what changes is nothing we say. So, now we say, “And the universe is expanding faster and faster—" Well, okay. That is our current picture, that is what we know and we’re trying to tell you the right story, but it would only take some very tiny deviation from the cosmological constant as the dark energy to produce a completely different affect. So, if there’s some slight, teeny little difference which we haven’t been able to measure, it could mean that the universe will expand for a while and then collapse in the future, or expand faster than exponentially, in which case things will get completely ripped apart. All of these weird things are possible, but our ability to measure them is really quite limited. 

So it probably is a little bit better for us to be more modest about what we do know and what we can predict and what we can be sure is really going to happen. But I think we’re at a very interesting state where the evidence has gotten better over time, that we really live in a universe that’s really accelerating. The implication is that there is this stuff, this dark energy really, a negative pressure of something or other, in the universe. But you know, something that is related to the nature of gravity that we really don’t understand. There’s a big piece of fundamental physics that is missing. And this, in a way is great because it’s when you know everything and when everything is understood and it all fits together, that’s sort of a sign of something that’s done. Move on to something else. 

When things don’t fit together and don’t quite make sense and you know that there’s a problem here, that’s great because of course, it means there’s going to be progress on this subject. The trouble is we don’t know when. And we don’t know which idea – at the moment, we don’t know which of the many ideas is really going to be the one that helps us solve this problem. 

It probably will seem like a nutty idea when it’s new, you know, when we first hear about it, but that doesn’t mean that all nutty ideas are right. It just means we don’t have to figure out which of these things is really right. And to do that, we want to do big surveys to measure more precisely how the universe has been expanding. We want to measure precisely how matter has clumped together under the force of gravity. We want to study this history that’s available to us using telescopes to really see what the constraints are on this weird thing, this dark energy that seems so important. But that we really have very little grip on to – we have very little grip to tell which ideas are right and which ideas are wrong.  And really, that’s what science is all about, is to pick out from the speculation and the kind of imagination which things agree with nature and so far, the measurements that we’ve made are kind of crude and we’ve got to do better.

Recorded on February 17, 2010
Interviewed by Austin \r\nAllen


Not all nutty ideas are good science, says Robert Kirshner. But there’s a mystery in physics whose solution, when it arrives, will probably sound pretty weird at first.

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

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  • Duke University researchers created a hydrogel that appears to be as strong and flexible as human cartilage.
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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
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  • 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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