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Scientists discover strange new shape called the ‘scutoid’

Scientists have identified a new shape called the scutoid, and it helps explain the how cells in the body arrange themselves in tightly packed three-dimensional structures to form tissues.

A 3D-printed design of a scutoid. (Credit: mathgrrl via Thingiverse)


Scientists have identified a new shape called the scutoid, a discovery that helps explain how cells arrange themselves in tightly packed three-dimensional structures that serve as protective barriers in the body.

The shape was discovered while a team of researchers was studying epithelial cells, which are the safety shields of the body that make up the cell walls lining our blood vessels and organs. As tissues and organs develop, epithelial cells squish together, twisting and turning into highly efficient and complex three-dimensional structures that help block microbes from entering our skin or organs.

But the shape of these cell structures has long been a mystery to scientists. Some have proposed they were shaped like prisms or cylinders, but a new paper published in Nature shows how scientists used computer modeling and imaging to settle the question once and for all.

The team ran a computer model to see what would be the most efficient shape for the epithelial cells to take. It produced a strange, prism-like shape, one with six sides on one end, five on the other, and a strange triangular protrusion coming out of one of the sides.


“It was such a surprise!” Luis Escudero, a developmental biologist at the University of Seville in Spain and co-author of the paper, told Gizmodo.

That was just a computer model, though. To find out if the strange shape exists in nature, the researchers used microcopy and computer imaging to take an up-close look at the epithelial tissues of fruit flies and zebrafish. As predicted, they discovered the scutoid. The name was chosen by Javier Buceta, a systems biologist and co-author of the study, because the shape resembles a beetle’s scutellum from a top-down view.


 

“You normally don’t have the opportunity in your life to name something that will hopefully be there forever,” Buceta told Gizmodo. “It’s not going to be the circle or the square, but we have been able to name a new shape.”

The researchers think the scutoid will be useful in other fields beyond biology, such as mathematics and engineering.

“We believe that this is a major breakthrough in many ways,” Escudero told Gizmodo. “We are convinced that there are more implications that we are trying to understand as we speak.”

The structures are tiny and difficult to image in 3D, so it’s still a mystery as to whether scutoids exist in the human body, but given its highly efficient form some think it’s likely.

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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A new hydrogel might be strong enough for knee replacements

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

Lee Jae-Sung of Korea Republic lies on the pitch holding his knee during the 2018 FIFA World Cup Russia group F match between Korea Republic and Germany at Kazan Arena on June 27, 2018 in Kazan, Russia.

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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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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