thescientist--2020-11-12--Slideshow: Solving a Gray Whale Murder Mystery

ABOVE : Researchers investigate the death of a gray whale that washed up at Angel Island State Park , California , in the spring of 2019 .
CARA FIELD / © THE MARINE MAMMAL CENTER UNDER NOAA FISHERIES MARINE MAMMAL HEALTH AND STRANDING RESPONSE PROGRAM PERMIT 18786-03 More than 360 gray whales have washed ashore in less than two years , leading researchers to ask what might be causing their demise .
Autopsying the dead animals and watching live whales on their migration routes suggest that there may not be a single culprit .
Instead , a combination of interacting @ @ @ @ @ @ @ in fishing gear , killer whale attacks , a balloon in population , and climate change , may be causing the uptick in gray whale deaths .
This stranded dead gray whale washed ashore in early April 2019 at Leadbetter Point State Park in Washington State .
After a necropsy , scientists concluded that it was unusually thin .
Researchers are still trying to determine why many of the whales that have shown up on a beach appear to be underweight .
Data on the whales doesn ’ t only come from dead @ @ @ @ @ @ @ whales gives clues to their health , too .
If a whale has a significant dip behind its head ( top ) , scientists think the whale is skinny and in poor health , but if there is no dip ( bottom ) , the whale is considered healthy .
THE LAGUNA SAN IGNACIO ECOSYSTEM SCIENCE PROGRAM , A PROJECT OF THE OCEAN FOUNDATION Counting the cow-calf pairs helps researchers track and estimate the overall population of gray whales as they migrate from the waters off the west coast of Mexico to the @ @ @ @ @

ABOVE: Researchers investigate the death of a gray whale that washed up at Angel Island State Park, California, in the spring of 2019.
CARA FIELD / © THE MARINE MAMMAL CENTER UNDER NOAA FISHERIES MARINE MAMMAL HEALTH AND STRANDING RESPONSE PROGRAM PERMIT 18786-03
More than 360 gray whales have washed ashore in less than two years, leading researchers to ask what might be causing their demise. Autopsying the dead animals and watching live whales on their migration routes suggest that there may not be a single culprit. Instead, a combination of interacting factors, including ship strikes, entanglement in fishing gear, killer whale attacks, a balloon in population, and climate change, may be causing the uptick in gray whale deaths.
Read the full story.
This stranded dead gray whale washed ashore in early April 2019 at Leadbetter Point State Park in Washington State. After a necropsy, scientists concluded that it was unusually thin. Researchers are still trying to determine why many of the whales that have shown up on a beach appear to be underweight. JOHN WELDON, NORTHERN OREGON/SOUTHERN WASHINGTON MARINE MAMMAL STRANDING PROGRAM UNDER NOAA FISHERIES MARINE MAMMAL HEALTH AND STRANDING RESPONSE PROGRAM PERMIT 18786-03
A necropsy of this gray whale stranded near Long Beach, Washington, showed that it, too, was skinny and malnourished. JOHN WELDON, PORTLAND STATE UNIVERSITY NORTHWEST OREGON/SOUTHERN WASHINGTON MARINE MAMMAL STRANDING PROGRAM UNDER NOAA FISHERIES MARINE MAMMAL HEALTH AND STRANDING RESPONSE PROGRAM PERMIT 18786-03
In April 2019, this female gray whale washed ashore at California’s Point Reyes National Seashore, and researchers were there to investigate. BARBIE HALASKA, THE MARINE MAMMAL CENTER
Data on the whales doesn’t only come from dead animals. The anatomy of the living whales gives clues to their health, too. If a whale has a significant dip behind its head (top), scientists think the whale is skinny and in poor health, but if there is no dip (bottom), the whale is considered healthy. THE LAGUNA SAN IGNACIO ECOSYSTEM SCIENCE PROGRAM, A PROJECT OF THE OCEAN FOUNDATION
At the Piedras Blancas field station near San Simeon, California, a team of scientists uses high-powered binoculars to scan for gray whale cows and their calves. NOAA FISHERIES


thescientist--2020-11-25--The Promise of mRNA Vaccines

The Promise of mRNA Vaccines

Earlier this month , the world finally received some good news about COVID-19 .
Interim results from Phase 3 clinical trials revealed that two vaccine candidates —one from the Pfizer and BioNTech and another from Moderna—were more than 90 percent effective .
In addition to sharing what appears to be very high efficacy , the vaccines have something else in common : they are both made with messenger RNA ( mRNA ) .
mRNA vaccines work by providing the genetic code for our cells to produce viral proteins .
Once the proteins , which don ’ t cause disease , @ @ @ @ @ @ @ immune response against the virus , enabling the person to develop immunity .
mRNA can theoretically be used to produce any protein , with the upside that it much simpler to manufacture than the proteins themselves or the inactivated and attenuated versions of viruses typically used in vaccines , making it an appealing technique , says Norbert Pardi , an mRNA vaccine specialist at the University of Pennsylvania .
The concept of using mRNA to produce useful proteins to fight disease has been around for decades .
But until now , no vaccines @ @ @ @ @ @ @ far in clinical trials .
The success of the SARS-CoV-2 vaccines “ is really good for the RNA field , because until very recently , there were just a handful of people who really believed in mRNA vaccines , ” Pardi tells The Scientist .
“ We now have the chance to really prove [ their usefulness ] in an actual outbreak situation.
” In an early proof-of-concept of using gene-based therapeutics to produce the proteins needed to fight disease , published in 1990 , scientists reported that in mice , cells successfully @ @ @ @ @ @ @ DNA .
The method was potentially revolutionary : It could , in theory , be used to engineer any protein the body needed to boost immunity against pathogens and fight diseases such as cancer and rare genetic conditions .
Despite its promise , there are challenges associated with working with mRNA .
Ordinary mRNA produces only low levels of proteins , and the molecule degrades too quickly inside the body to make it suitable as a therapeutic .
On top of that , RNA can trigger an immune response that ’ s independent @ @ @ @ @ @ @ encodes .
“ If you just inject foreign RNA into people or animals , you can induce a very serious inflammatory response , ” Pardi says .
He adds that this is our bodies ’ defense mechanism against viruses , which can use either DNA or RNA to store their genetic information .
Because of these problems , the uptake of this technology was slow , and many scientists chose to instead focus on developing vaccines with DNA , which is more stable and easier to work with , says Margaret Liu , @ @ @ @ @ @ @ International Society for Vaccines and a pioneer of gene-based vaccines .
( Liu is on scientific advisory board of the University of Oxford ’ s Jenner Institute , which developed AstraZeneca ’ s vaccine for COVID-19 . )
A few key technological advances have contributed to the success of the SARS-CoV-2 vaccines from Moderna and Pfizer/BioNTech .
In the early 2000s , mRNA vaccines got a boost when a pair of scientists at the University of Pennsylvania , Katalin Karikó and Drew Weissman , discovered that by altering the building blocks of RNA—nucleosides—they @ @ @ @ @ @ @ the technique .
In a seminal 2005 paper , they reported that modified , synthetic nucleosides could both increase protein production from the mRNA and drastically suppress the immune system ’ s reaction to the mRNA molecules themselves .
( Karikó is now a senior vice president at BioNTech . )
“ I think pretty much everyone acknowledges this as the big breakthrough [ for mRNA vaccines ] , ” says Liu .
Scientists still needed a method to fortify the mRNA against rapid degradation after injection , however .
Pardi , along @ @ @ @ @ @ @ a solution : by encasing mRNA in small bubbles of fat known as lipid nanoparticles ( LNPs ) , they were able to protect the molecule and enhance its delivery into cells .
“ The really difficult challenge for the field for the last at least four to five years has been the delivery [ of the mRNA ] , ” says Nick Jackson , the head of programs and technology at the Coalition for Epidemic Preparedness Innovations ( CEPI ) , an organization providing funding for many SARS-CoV-2 vaccines , including Moderna @ @ @ @ @ @ @ really been thanks to the incredible innovation around LNPs that has finally shown the validation of this platform and opens the floodgates to mRNA potential.
” Scientists have clinically tested mRNA vaccines for a wide range of infectious diseases , including rabies , influenza , and Zika .
Until now , none have made it past small , early-phase clinical trials .
The two SARS-CoV-2 vaccines are “ by far the most advanced , ” Liu tells The Scientist .
“ None [ of the others ] were as promising as what we @ @ @ @ @ @ @ the SARS-COV-2 vaccines from Pfizer/BioNtech and Moderna far exceeded expectations .
The reported efficacy of more than 90 percent for both surpasses the US Food and Drug Administration ’ s 50 percent efficacy cutoff for considering a vaccine for emergency use authorization ( EUA ) .
The results for Pfizer and BioNTech ’ s vaccine “ are really quite good , I mean extraordinary , ” Anthony Fauci , the director of the National Institute of Allergy and Infectious Diseases ( NIAID ) told The Washington Post earlier this month .
( NIAID @ @ @ @ @ @ @ mRNA vaccine . )
Why these vaccines seem so effective while previous attempts against other pathogens haven ’ t appeared as promising remains an open question .
One simple reason , according to Liu , might be the sheer volume of resources that were poured into developing them .
Liu also hypothesizes that one explanation for the high levels of efficacy is that the vaccines might be triggering a nonspecific inflammatory response to the mRNA that could be heightening its specific immune response , given that the modified nucleoside technique reduced inflammation but @ @ @ @ @ @ @ On the flip side , she adds , this may also explain the intense reactions such as aches and fevers reported in some recipients of the mRNA SARS-CoV-2 vaccines .
( Others have suggested that the lipid nanoparticle is responsible for these severe , but transient , side effects reported in some trial participants . )
Ultimately , it ’ s too early to say why these vaccines so far appear to work so well .
“ These do remain interim results .
They do remain unpublished .
And we still need to @ @ @ @ @ @ @ these products , ” Jackson says .
There are also issues to sort out , such as concerns about needing to store the vaccines in freezers—especially in the case of the Pfizer/BioNTech vaccine , which needs to be kept at –70 °C .
( Another mRNA vaccine against SARS-CoV-2 , developed by the German company CureVac , can be stored at 5 °C .
That vaccine , which is based on non-modified mRNA , is in a Phase I clinical trial . )
Still , the early success of the mRNA vaccines for @ @ @ @ @ @ @ of this technology .
“ These are really exciting times for RNA vaccines , ” Pardi tells The Scientist .
In addition to applications in infectious diseases , researchers in both academia and industry have been pursuing the use of mRNA vaccines to harness the immune system to fight cancer .
One of the biggest benefits of the mRNA platform is its flexibility , Pardi says—for example , he is currently investigating ways to encode multiple viral proteins into a single vaccine , which could help produce a more potent immune response against @ @ @ @ @ @ @ have revealed their potential , many more vaccine makers will likely develop an interest in the technique , according to Jackson .
“ I would predict , and others have too , that this will beckon a new era for the application of mRNA towards infectious diseases , particularly as rapid response platforms to help deal with outbreaks .
”

ABOVE: © ISTOCK.COM, SERHEII YAKOVLIEV
Earlier this month, the world finally received some good news about COVID-19. Interim results from Phase 3 clinical trials revealed that two vaccine candidates—one from the Pfizer and BioNTech and another from Moderna—were more than 90 percent effective. In addition to sharing what appears to be very high efficacy, the vaccines have something else in common: they are both made with messenger RNA (mRNA).
mRNA vaccines work by providing the genetic code for our cells to produce viral proteins. Once the proteins, which don’t cause disease, are produced, the body launches an immune response against the virus, enabling the person to develop immunity. mRNA can theoretically be used to produce any protein, with the upside that it much simpler to manufacture than the proteins themselves or the inactivated and attenuated versions of viruses typically used in vaccines, making it an appealing technique, says Norbert Pardi, an mRNA vaccine specialist at the University of Pennsylvania.
The concept of using mRNA to produce useful proteins to fight disease has been around for decades. But until now, no vaccines using this technology have made it this far in clinical trials. The success of the SARS-CoV-2 vaccines “is really good for the RNA field, because until very recently, there were just a handful of people who really believed in mRNA vaccines,” Pardi tells The Scientist. “We now have the chance to really prove [their usefulness] in an actual outbreak situation.”
Overcoming obstacles to mRNA vaccines
In an early proof-of-concept of using gene-based therapeutics to produce the proteins needed to fight disease, published in 1990, scientists reported that in mice, cells successfully produced proteins encoded in injected RNA or DNA. The method was potentially revolutionary: It could, in theory, be used to engineer any protein the body needed to boost immunity against pathogens and fight diseases such as cancer and rare genetic conditions.
I would predict, and others have too, that this will beckon a new era for the application of mRNA towards infectious diseases, particularly as rapid response platforms to help deal with outbreaks. —Nick Jackson, Coalition for Epidemic Preparedness Innovations (CEPI)
Despite its promise, there are challenges associated with working with mRNA. Ordinary mRNA produces only low levels of proteins, and the molecule degrades too quickly inside the body to make it suitable as a therapeutic. On top of that, RNA can trigger an immune response that’s independent of the response to the protein it encodes. “If you just inject foreign RNA into people or animals, you can induce a very serious inflammatory response,” Pardi says. He adds that this is our bodies’ defense mechanism against viruses, which can use either DNA or RNA to store their genetic information.
Because of these problems, the uptake of this technology was slow, and many scientists chose to instead focus on developing vaccines with DNA, which is more stable and easier to work with, says Margaret Liu, the chairman of the board of the International Society for Vaccines and a pioneer of gene-based vaccines. (Liu is on scientific advisory board of the University of Oxford’s Jenner Institute, which developed AstraZeneca’s vaccine for COVID-19.)
A few key technological advances have contributed to the success of the SARS-CoV-2 vaccines from Moderna and Pfizer/BioNTech. In the early 2000s, mRNA vaccines got a boost when a pair of scientists at the University of Pennsylvania, Katalin Karikó and Drew Weissman, discovered that by altering the building blocks of RNA—nucleosides—they could address some of key limitations of the technique. In a seminal 2005 paper, they reported that modified, synthetic nucleosides could both increase protein production from the mRNA and drastically suppress the immune system’s reaction to the mRNA molecules themselves. (Karikó is now a senior vice president at BioNTech.)
“I think pretty much everyone acknowledges this as the big breakthrough [for mRNA vaccines],” says Liu.
Scientists still needed a method to fortify the mRNA against rapid degradation after injection, however. Pardi, along with Karikó and Weissman, helped identify a solution: by encasing mRNA in small bubbles of fat known as lipid nanoparticles (LNPs), they were able to protect the molecule and enhance its delivery into cells.
“The really difficult challenge for the field for the last at least four to five years has been the delivery [of the mRNA],” says Nick Jackson, the head of programs and technology at the Coalition for Epidemic Preparedness Innovations (CEPI), an organization providing funding for many SARS-CoV-2 vaccines, including Moderna’s. “It’s really been thanks to the incredible innovation around LNPs that has finally shown the validation of this platform and opens the floodgates to mRNA potential.”
“Exciting times for RNA vaccines”
Scientists have clinically tested mRNA vaccines for a wide range of infectious diseases, including rabies, influenza, and Zika. Until now, none have made it past small, early-phase clinical trials. The two SARS-CoV-2 vaccines are “by far the most advanced,” Liu tells The Scientist. “None [of the others] were as promising as what we’ve seen.”
In fact, the SARS-COV-2 vaccines from Pfizer/BioNtech and Moderna far exceeded expectations. The reported efficacy of more than 90 percent for both surpasses the US Food and Drug Administration’s 50 percent efficacy cutoff for considering a vaccine for emergency use authorization (EUA).
The results for Pfizer and BioNTech’s vaccine “are really quite good, I mean extraordinary,” Anthony Fauci, the director of the National Institute of Allergy and Infectious Diseases (NIAID) told The Washington Post earlier this month. (NIAID collaborated with Moderna on the other SARS-CoV-2 mRNA vaccine.)
Why these vaccines seem so effective while previous attempts against other pathogens haven’t appeared as promising remains an open question. One simple reason, according to Liu, might be the sheer volume of resources that were poured into developing them. Liu also hypothesizes that one explanation for the high levels of efficacy is that the vaccines might be triggering a nonspecific inflammatory response to the mRNA that could be heightening its specific immune response, given that the modified nucleoside technique reduced inflammation but hasn’t eliminated it completely. On the flip side, she adds, this may also explain the intense reactions such as aches and fevers reported in some recipients of the mRNA SARS-CoV-2 vaccines. (Others have suggested that the lipid nanoparticle is responsible for these severe, but transient, side effects reported in some trial participants.)
Ultimately, it’s too early to say why these vaccines so far appear to work so well. “These do remain interim results. They do remain unpublished. And we still need to see the extensive safety databases associated with these products,” Jackson says. There are also issues to sort out, such as concerns about needing to store the vaccines in freezers—especially in the case of the Pfizer/BioNTech vaccine, which needs to be kept at –70 °C. (Another mRNA vaccine against SARS-CoV-2, developed by the German company CureVac, can be stored at 5 °C. That vaccine, which is based on non-modified mRNA, is in a Phase I clinical trial.)
Still, the early success of the mRNA vaccines for COVID-19 have scientists optimistic about the future of this technology. “These are really exciting times for RNA vaccines,” Pardi tells The Scientist. In addition to applications in infectious diseases, researchers in both academia and industry have been pursuing the use of mRNA vaccines to harness the immune system to fight cancer. One of the biggest benefits of the mRNA platform is its flexibility, Pardi says—for example, he is currently investigating ways to encode multiple viral proteins into a single vaccine, which could help produce a more potent immune response against a virus.
Now that mRNA vaccines have revealed their potential, many more vaccine makers will likely develop an interest in the technique, according to Jackson. “I would predict, and others have too, that this will beckon a new era for the application of mRNA towards infectious diseases, particularly as rapid response platforms to help deal with outbreaks.”


thescientist--2020-11-25--SARS-CoV-2 Genetic Variant May Be More Transmissible

Before March , most of the SARS-CoV-2 genomes that researchers worldwide isolated and sequenced encoded an aspartic acid ( D ) at residue 614 of the viral spike protein .
By April , the majority of viral sequences harbored a single mutation in the genome converting the D to a glycine ( G ) .
Presently , the 614D variant has been all but replaced by the 614G variant globally .
These findings , described in a study published in Cell in August , and corroborating evidence from other groups have led scientists around the world to investigate whether the @ @ @ @ @ @ @ strains is based on random introduction by a group of mobile founders or if it indicates that 614G provides some sort of selective advantage to the virus—making it more infective , for instance .
An answer to this question would have big importance to addressing the pandemic , according to Jessica Plante , a virologist at the World Reference Center for Emerging Viruses and Arboviruses at the University of Texas Medical Branch , because “ a random event is unlikely to have massive epidemiological consequences.
” On the other hand , she says @ @ @ @ @ @ @ more infectious , or if the virus is causing more severe disease , that ’ s something that we need to be able to verify very quickly , so that the public health side can realize that a more contagious or a more severe form of the virus is now spreading.
” Several studies published this fall point to the latter , that 614G transmits more readily than 614D .
In a paper published in Cell November 18 , researchers evaluated more than 25,000 whole genome SARS-CoV-2 sequences collected in the United Kingdom @ @ @ @ @ @ @ other places , 614G became the dominant variant in late March in the UK , after multiple independent introductions , mostly from people who had traveled internationally .
The authors also confirmed that 614G is not associated with infection severity and observed that younger patients were more likely to have 614G and have higher viral loads .
Their results support the idea that 614G is under positive selection and likely affects virus transmissibility .
“ Even with that massive data set , we were almost pushing the limit of the ability to identify @ @ @ @ @ @ @ coauthor Thomas Connor , a genetic epidemiologist at Cardiff University in Wales , tells The Scientist .
Detecting such a subtle change in infectivity would be much more difficult with a smaller sample size .
“ A lot of groups—including [ in ] this study , which is by far the largest sample number in any of the studies published to date—were looking at the increase in this particular variant over time .
But what makes this new study really exciting is that they had done it all within a small population , @ @ @ @ @ @ @ rather than amassing samples from around the world , which increases the possibility of additional confounders , says Judd Hultquist , an infectious disease researcher at Northwestern Memorial Hospital , who did not participate in the work .
“ Their ability to sample this particular population with great depth allowed them to track multiple independent introductions of the same viral variant into the population , ” he writes in an email to The Scientist .
“ Seeing the same trend emerge after multiple independent introductions allowed them to make conclusions about how these @ @ @ @ @ @ @ they suggest is that the patterns that we see are consistent with a selective advantage , and that this gene mutation arose and has now dominated because it is likely an adaptation [ to ] humans , ” says Nathan Grubaugh , an epidemiologist at the Yale School of Public Health who did not participate in the work .
“ We ’ ve seen in the past where you have something from an animal population that spills over into humans , it ’ s going to slightly adapt to be better in the @ @ @ @ @ @ @ 614G could be due to the production of more virus during infection .
Hultquist ’ s group published a paper November 11 showing that patients infected with the 614G variant had higher viral loads in their upper airways than did patients with 614D .
The findings hold up in animal models , too .
Plante and her colleagues showed in a study in October that hamsters infected with the 614G variant had higher viral loads in the upper respiratory tract , but not in the lungs , than did animals with 614D .
@ @ @ @ @ @ @ could lead to increased transmission .
“ It ’ s speculated that the more virus you have , the more contagious you might be to somebody else , ” says Grubaugh .
“ And in principle that makes sense , but in reality that ’ s also a hard thing to prove or disprove.
” The next question is to determine in a transmission model whether the 614G variant really is more infectious , Hultquist says .
“ Multiple independent groups have now collected data that is consistent with the 614G variant of @ @ @ @ @ @ @ it still hasn ’ t been proven that the virus is more transmissible.
” Martin Beer , a virologist at the Friedrich Loeffler Institute in Germany , and colleagues released a preprint on October 27 that includes a head-to-head comparison of 614G and 614D in ferret and hamster models of viral transmission .
“ In this competition experiment , with a 50/50 mixture , the 614G out-competed the 614D in most cases , ” he says .
Taking all these various lines of evidence from the lab and epidemiological observations of the pandemic @ @ @ @ @ @ @ now .
.
.
that this is most likely not a founder effect .
This is probably a real advantage for the virus , ” Beer says .
But to which extent the 614G variant is more easily transmitted under real-world conditions is a difficult task , he adds .
“ 614G is for sure not less efficient than the 614D .
There is a good chance that it is more efficient—for example , in a ‘ super spreader ’ event.
” Because multiple groups have shown that neither form has “ an @ @ @ @ @ @ @ of , on disease severity , knowing what virus you ’ re infected with won ’ t impact your treatment regimen or whether or not you will be protected from a vaccine , or whether the drugs will work , ” says Grubaugh .
“ The things that [ people ] can do to protect themselves from one variant or another variant are all the same , ” agrees Hultquist .
“ Wear a mask .
Be cognizant of your social distancing .
Wash your hands regularly , and follow local public health @ @ @

ABOVE: © ISTOCK.COM,
FREEZELIGHT
Before March, most of the SARS-CoV-2 genomes that researchers worldwide isolated and sequenced encoded an aspartic acid (D) at residue 614 of the viral spike protein. By April, the majority of viral sequences harbored a single mutation in the genome converting the D to a glycine (G). Presently, the 614D variant has been all but replaced by the 614G variant globally.
These findings, described in a study published in Cell in August, and corroborating evidence from other groups have led scientists around the world to investigate whether the rapid shift in representation of circulating viral strains is based on random introduction by a group of mobile founders or if it indicates that 614G provides some sort of selective advantage to the virus—making it more infective, for instance.
An answer to this question would have big importance to addressing the pandemic, according to Jessica Plante, a virologist at the World Reference Center for Emerging Viruses and Arboviruses at the University of Texas Medical Branch, because “a random event is unlikely to have massive epidemiological consequences.” On the other hand, she says, “if the virus is truly more infectious, or if the virus is causing more severe disease, that’s something that we need to be able to verify very quickly, so that the public health side can realize that a more contagious or a more severe form of the virus is now spreading.”
Several studies published this fall point to the latter, that 614G transmits more readily than 614D.
In a paper published in Cell November 18, researchers evaluated more than 25,000 whole genome SARS-CoV-2 sequences collected in the United Kingdom between January and June. As in other places, 614G became the dominant variant in late March in the UK, after multiple independent introductions, mostly from people who had traveled internationally. The authors also confirmed that 614G is not associated with infection severity and observed that younger patients were more likely to have 614G and have higher viral loads. Their results support the idea that 614G is under positive selection and likely affects virus transmissibility.
“Even with that massive data set, we were almost pushing the limit of the ability to identify that this effect was there,” coauthor Thomas Connor, a genetic epidemiologist at Cardiff University in Wales, tells The Scientist. Detecting such a subtle change in infectivity would be much more difficult with a smaller sample size.
What they suggest is that the patterns that we see are consistent with a selective advantage, and that this gene mutation arose and has now dominated because it is likely an adaptation [to] humans. —Nathan Grubaugh, Yale School of Public Health
“A lot of groups—including [in] this study, which is by far the largest sample number in any of the studies published to date—were looking at the increase in this particular variant over time. But what makes this new study really exciting is that they had done it all within a small population, so all within the UK,” rather than amassing samples from around the world, which increases the possibility of additional confounders, says Judd Hultquist, an infectious disease researcher at Northwestern Memorial Hospital, who did not participate in the work.
“Their ability to sample this particular population with great depth allowed them to track multiple independent introductions of the same viral variant into the population,” he writes in an email to The Scientist. “Seeing the same trend emerge after multiple independent introductions allowed them to make conclusions about how these different viral variants spread.”
“What they suggest is that the patterns that we see are consistent with a selective advantage, and that this gene mutation arose and has now dominated because it is likely an adaptation [to] humans,” says Nathan Grubaugh, an epidemiologist at the Yale School of Public Health who did not participate in the work. “We’ve seen in the past where you have something from an animal population that spills over into humans, it’s going to slightly adapt to be better in the system.”
That apparent heightened contagiousness of 614G could be due to the production of more virus during infection. Hultquist’s group published a paper November 11 showing that patients infected with the 614G variant had higher viral loads in their upper airways than did patients with 614D.
The findings hold up in animal models, too. Plante and her colleagues showed in a study in October that hamsters infected with the 614G variant had higher viral loads in the upper respiratory tract, but not in the lungs, than did animals with 614D. They hypothesize that these higher viral loads could lead to increased transmission.
“It’s speculated that the more virus you have, the more contagious you might be to somebody else,” says Grubaugh. “And in principle that makes sense, but in reality that’s also a hard thing to prove or disprove.”
The next question is to determine in a transmission model whether the 614G variant really is more infectious, Hultquist says. “Multiple independent groups have now collected data that is consistent with the 614G variant of the virus being more transmissible, but it still hasn’t been proven that the virus is more transmissible.”
Martin Beer, a virologist at the Friedrich Loeffler Institute in Germany, and colleagues released a preprint on October 27 that includes a head-to-head comparison of 614G and 614D in ferret and hamster models of viral transmission. “In this competition experiment, with a 50/50 mixture, the 614G out-competed the 614D in most cases,” he says.
Taking all these various lines of evidence from the lab and epidemiological observations of the pandemic together, “there is an indication now . . . that this is most likely not a founder effect. This is probably a real advantage for the virus,” Beer says. But to which extent the 614G variant is more easily transmitted under real-world conditions is a difficult task, he adds. “614G is for sure not less efficient than the 614D. There is a good chance that it is more efficient—for example, in a ‘super spreader’ event.”
Because multiple groups have shown that neither form has “an impact, at least that we know of, on disease severity, knowing what virus you’re infected with won’t impact your treatment regimen or whether or not you will be protected from a vaccine, or whether the drugs will work,” says Grubaugh.
“The things that [people] can do to protect themselves from one variant or another variant are all the same,” agrees Hultquist. “Wear a mask. Be cognizant of your social distancing. Wash your hands regularly, and follow local public health guidelines.”


thescientist--2020-11-25--Q&A: How Animals Change in Space

Q&A: How Animals Change in Space

Humans have been traveling out of the Earth ’ s atmosphere to explore the near-reaches of our solar system for decades , but biologists have only a rudimentary understanding of how this influences astronauts ’ health , says Christopher Mason , a geneticist at Weill Cornell Medicine .
A collection of more than a dozen studies authored by more than 200 scientists , published today ( November 25 ) in Cell Press journals , aims to characterize the molecular and cellular changes that occur as a result of spaceflight .
“ It ’ s a little bit preposterous to have @ @ @ @ @ @ @ , ” admits Mason , who says there ’ s more on the way .
“ But it ’ s a big unknown question so we wanted to address it with a lot of data.
” The Scientist spoke with Mason , a coauthor on nine of the new papers and a review of the collection , to learn more about the research .
The Scientist : In the press release I got from Cell Press , it says this is “ the largest set of astronaut data and space biology data ever @ @ @ @ @ @ @ ?
Christopher Mason : A lot of this was inspired by some early work with the NASA Twin Study , which started in 2014. .
.
.
Continuously throughout that study , we kept observing intriguing biochemical , physiological , genetic , and even cognitive changes that were occurring due to being in space for a year .
.
.
.
Every time we saw something interesting in the Twin Study , that was in [ astronauts ] Scott versus Mark [ Kelly ] , we immediately wanted to think , well , @ @ @ @ @ @ @ we see the same thing in them ?
Do we see it to the same degree ?
.
.
.
And how much can we see this across other organisms ?
.
.
.
A lot of these questions we really had no idea of what any of those answers would be .
But then I ’ m also on the steering committee for the GeneLab group .
Have you heard of GeneLab before ?
CM : It ’ s NASA ’ s repository of basically anything that ’ s nonhuman that ’ @ @ @ @ @ @ @ profiled in any way , say , gene expression profiling , epigenetics , any way you ’ ve done a characterization of the sample .
.
.
.
And so I had a student in 2016 and ’ 17 who started building an API [ application programming interface ] so we could do rapid queries of those data sets .
And so that ’ s some of the genesis [ of this new collection ] : fundamentally , the big question was , Is there something we can learn about a set of @ @ @ @ @ @ @ spaceflight ?
.
.
.
And so this was the bridge data from 59 astronauts , as well as any mouse or rat or any organism that ’ s ever been flown in space that ’ s been characterized up there and when it got back .
So it was to try and think , what are the consistent features of spaceflight , so we can begin to address them with countermeasures and future studies .
TS : Which of the collection studies do you find most exciting ?
CM : I really @ @ @ @ @ @ @ same microRNAs that we observed in Scott Kelly when he was up in space also were observed in some of the mouse models and also what ’ s called the hindlimb unloading models , where you actually try and simulate microgravity on Earth as best you can .
But some of the same signatures would show up from mouse models in space , from mouse models on Earth , and also in astronauts in flight .
And what ’ s really cool is that it seemed to be if you control the regulation @ @ @ @ @ @ @ prevent some of the radiation-dependent damage .
The other ones I really like .
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As identical twins , [ Mark and Scott Kelly are ] becoming less identical as each day passes .
And that ’ s because one of the things we discovered in the sequencing of their genomes in their blood cells is they each have different mutations [ known to increase the risks of cardiovascular disease , cancer , and other health outcomes ] .
Which is not surprising .
As every cell divides , you get @ @ @ @ @ @ @ .
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.The mutations that we found in Scott before his flight , they actually were slightly improved [ became less abundant ] as a consequence of spaceflight .
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but then came back up after he got back to Earth— [ an effect now also seen in other astronauts ] .
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So we proposed in the paper that this is something that ’ s relatively easy to do—it ’ s just with a blood draw—and gives you a quantitative measure of some of the genetic risk long-term for @ @ @ @ @ @ @ additional grant to study this for more astronauts from NASA .
[ In another study , we found that astronauts ’ ] telomeres got longer [ while in space ] .
And then we led a study to get samples from the top of Mount Everest—it ’ s basically the closest you can get to the space station while you ’ re on Earth , and also it ’ s a hypoxic environment that has more radiation and is high stress .
And they also showed longer telomeres and oxidative damage when they @ @ @ @ @ @ @ .
TS : How do you see these results being applied ?
What are you learning that will enable or improve human spaceflight going forward ?
CM : The clonal hematopoiesis [ method ] is becoming a standard of care at most cancer centers around the country and around the world .
And so this idea of using highly sensitive genetic mapping technology to see , is someone carrying a mutation .
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the grant we just got from NASA is to continue to do that work for future astronauts .
NASA @ @ @ @ @ @ @ which is , what are the things that you should be continually measuring for astronauts ?
And I think this will become one of those metrics .
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Some of the methods [ we used for ] long-read sequencing and also ways to measure telomeres , those are new methods that will be used for future astronauts .
And one of the papers , we put a list of all the potential pharmacological interventions you could use [ to prevent or counteract some of the damage done to human cells and @ @ @ @ @ @ @ , we found a lot of the changes in the cytokines in Scott when he landed were really rough on his body .
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Like IL-6 , for example , which you may have seen in the news , because that ’ s something that is really elevated in COVID patients .
So we think some of the same stressors [ of space travel ] have a really intriguing intersection with other infections or severe stressors on the body .
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I think the astronaut studies can inform the @ @ @ @ @ @ @ astronauts studies , and serve as kind of a back-and-forth enrichment of knowledge that could help in both contexts .

ABOVE: NASA
Humans have been traveling out of the Earth’s atmosphere to explore the near-reaches of our solar system for decades, but biologists have only a rudimentary understanding of how this influences astronauts’ health, says Christopher Mason, a geneticist at Weill Cornell Medicine. A collection of more than a dozen studies authored by more than 200 scientists, published today (November 25) in Cell Press journals, aims to characterize the molecular and cellular changes that occur as a result of spaceflight.
“It’s a little bit preposterous to have so much come out all at once,” admits Mason, who says there’s more on the way. “But it’s a big unknown question so we wanted to address it with a lot of data.”
The Scientist spoke with Mason, a coauthor on nine of the new papers and a review of the collection, to learn more about the research.
The Scientist: In the press release I got from Cell Press, it says this is “the largest set of astronaut data and space biology data ever produced.” How did this come about?
Christopher Mason THE PERSHING FOUNDATION
Christopher Mason: A lot of this was inspired by some early work with the NASA Twin Study, which started in 2014. . . . Continuously throughout that study, we kept observing intriguing biochemical, physiological, genetic, and even cognitive changes that were occurring due to being in space for a year. . . . Every time we saw something interesting in the Twin Study, that was in [astronauts] Scott versus Mark [Kelly], we immediately wanted to think, well, how frequent is this and other astronauts—do we see the same thing in them? Do we see it to the same degree? . . . And how much can we see this across other organisms? . . . A lot of these questions we really had no idea of what any of those answers would be. But then I’m also on the steering committee for the GeneLab group. Have you heard of GeneLab before?
TS: No, I haven’t.
CM: It’s NASA’s repository of basically anything that’s nonhuman that’s been flown to space and then profiled in any way, say, gene expression profiling, epigenetics, any way you’ve done a characterization of the sample. . . . And so I had a student in 2016 and ’17 who started building an API [application programming interface] so we could do rapid queries of those data sets. And so that’s some of the genesis [of this new collection]: fundamentally, the big question was, Is there something we can learn about a set of consistent features of the physiological response to spaceflight? . . . And so this was the bridge data from 59 astronauts, as well as any mouse or rat or any organism that’s ever been flown in space that’s been characterized up there and when it got back. So it was to try and think, what are the consistent features of spaceflight, so we can begin to address them with countermeasures and future studies.
TS: Which of the collection studies do you find most exciting?
CM: I really was excited to see some of the same microRNAs that we observed in Scott Kelly when he was up in space also were observed in some of the mouse models and also what’s called the hindlimb unloading models, where you actually try and simulate microgravity on Earth as best you can. But some of the same signatures would show up from mouse models in space, from mouse models on Earth, and also in astronauts in flight. And what’s really cool is that it seemed to be if you control the regulation of those microRNAs, you can actually prevent some of the radiation-dependent damage.
The other ones I really like. . . . As identical twins, [Mark and Scott Kelly are] becoming less identical as each day passes. And that’s because one of the things we discovered in the sequencing of their genomes in their blood cells is they each have different mutations [known to increase the risks of cardiovascular disease, cancer, and other health outcomes]. Which is not surprising. As every cell divides, you get what’s called somatic mutations. . . .The mutations that we found in Scott before his flight, they actually were slightly improved [became less abundant] as a consequence of spaceflight . . . but then came back up after he got back to Earth—[an effect now also seen in other astronauts]. . . . So we proposed in the paper that this is something that’s relatively easy to do—it’s just with a blood draw—and gives you a quantitative measure of some of the genetic risk long-term for the astronauts. We just got an additional grant to study this for more astronauts from NASA.
[In another study, we found that astronauts’] telomeres got longer [while in space]. And then we led a study to get samples from the top of Mount Everest—it’s basically the closest you can get to the space station while you’re on Earth, and also it’s a hypoxic environment that has more radiation and is high stress. And they also showed longer telomeres and oxidative damage when they were climbing the top of the mountain.
TS: How do you see these results being applied? What are you learning that will enable or improve human spaceflight going forward?
CM: The clonal hematopoiesis [method] is becoming a standard of care at most cancer centers around the country and around the world. And so this idea of using highly sensitive genetic mapping technology to see, is someone carrying a mutation . . . the grant we just got from NASA is to continue to do that work for future astronauts. NASA has something called the standard measures, which is, what are the things that you should be continually measuring for astronauts? And I think this will become one of those metrics. . . . Some of the methods [we used for] long-read sequencing and also ways to measure telomeres, those are new methods that will be used for future astronauts. And one of the papers, we put a list of all the potential pharmacological interventions you could use [to prevent or counteract some of the damage done to human cells and tissues in space].
In particular, we found a lot of the changes in the cytokines in Scott when he landed were really rough on his body. . . . Like IL-6, for example, which you may have seen in the news, because that’s something that is really elevated in COVID patients. So we think some of the same stressors [of space travel] have a really intriguing intersection with other infections or severe stressors on the body. . . . I think the astronaut studies can inform the terrestrial treatments and terrestrial treatments can inform astronauts studies, and serve as kind of a back-and-forth enrichment of knowledge that could help in both contexts.


thescientist--2020-11-24--COVID-19 Research Biased Toward Only a Handful of Genes

Scientists have identified more than 2,000 human genes linked to COVID-19 , yet the bulk of the published literature is dominated by only a small subset of them , a fact that may be limiting progress in the fight against the pandemic .
A team at Northwestern University , led by data scientist Thomas Stoeger , had previously shown that scientists tend to focus on a handful of genes—specifically , less than 20 percent of all genes in the human genome accounted for more than 90 percent of the publications they analyzed .
Prior to the Human Genome Project , @ @ @ @ @ @ @ full suite of human genes and relied more heavily on those that had analogs in model organisms or were easier to study using knockout experiments .
The advent of modern sequencing technology—including complementary tools such as CRISPR , mass spectrometry , and RNA-based approaches—has broadened what researchers know , but it seems that scientists are still holding to old patterns .
In a study published today ( November 24 ) in eLife , Stoeger and his Northwestern colleague Luís Amaral looked to COVID-19 research to see if scientists were similarly prioritizing certain genes @ @ @ @ @ @ @ research on mechanisms of infection and transmission , diagnostic tools , and treatments .
The pair analyzed 10,395 published papers and preprints and compared the genes studied in those publications against a list of genes linked to the virus through genome-wide association studies ( GWAS ) .
As the pandemic has progressed , they found , scientists have become focused on a small subset of genes to the exclusion of others that may also be important .
Of the roughly 2,000 genes identified by the GWAS reports , only 611 were included in @ @ @ @ @ @ @ , three genes , which code [ KG1 ] for angiotensin-converting enzyme 2 ( ACE2 ) , a receptor the virus uses to enter cells ; C-reactive protein , an inflammation marker ; and interleukin 6 , a signaling molecule involved in inflammatory responses , accounted for 25 percent of the total research .
When they compared these COVID-19 papers against a set of roughly 466,000 non–COVID-19 papers from before 2016 , Stoeger and Nunes discovered that whether or not the research related to the pandemic , the same types of genes—those advantageous @ @ @ @ @ @ @ The Scientist spoke with Stoeger about how researchers choose which genes to study , what information they could be missing , and ways that research can open up to previously overlooked genes .
The Scientist : In the paper , you mention this historical bias around the genes that scientists choose to focus on , and you talk about how these choices predate the Human Genome Project .
Can you describe how people were selecting genes to study prior to the Human Genome Project ?
Thomas Stoeger : Science is difficult , and @ @ @ @ @ @ @ research problems .
The research questions scientists worked on before the Human Genome Project tended to be on genes which are interesting and very useful to study , but also happened to be easier to study in a few different ways .
One way is that the human genes [ they chose ] also had related genes in model organisms , such as fruit flies or worms , and the related gene had already been studied .
The shortest genes have also been studied much more than others .
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because they @ @ @ @ @ @ @ And there are also some other chemical properties , for instance , the proteins encoded by the genes .
When proteins sit on the outside of the cell , for example , it ’ s easier to access them .
All of these things together made experimentation less difficult .
TS : How does this new paper build upon the previous work that you have done looking at this bias in gene choice for research ?
Stoeger : It ’ s our wish to capture all aspects of biology and make them interlinked @ @ @ @ @ @ @ to questions of chemistry [ and ] biology .
Conceptually , this paper is a little bit different from the last one .
The last one was mostly on things that were in the past .
Now , we want to know—for something very current where many scientists are all working on the same thing—to what extent [ do ] we stick to the same past bias or to what extent do we do something new ?
So maybe the better answer would be for me to say that we want to know @ @ @ @ @ @ @ the same biases that affect the rest of the medical literature .
TS : Can you tell me a little bit more about LitCovid , the program that you used to identify the genes being studied in COVID-19 research ?
Stoeger : I ’ m a data scientist who tries to integrate many different resources .
I ’ m always particularly thankful when other institutions have already cleaned the data and brought it into a very nice shape .
LitCovid is a curated list of publications that relate to COVID-19 [ managed by @ @ @ @ @ @ @ and they ’ ve already computationally tagged individual concepts within those articles .
You can imagine it as having all of the abstracts and titles and results , and whenever there is a word linked to a gene there is something inserted into the text that says , “ Here is a gene , ” and each gene has a unique number .
Computationally what they ’ re doing is using a type of natural language processing to make a model of how language works and making tags that relate to genes or @ @ @ @ @ @ @ allows people like myself to combine it with other data , such as data from the past or data from different experiments , to see how all of these different things relate together .
TS : What kinds of information might we be missing out on by focusing only on this small subset of genes ?
Stoeger : The honest answer is that we really don ’ t know .
We don ’ t know what all of these other genes that pop up in large experiments related to COVID-19 do .
Many @ @ @ @ @ @ @ COVID-19 literature are very important genes and should be studied , but they ’ re not the full story .
TS : How do scientists break out of this rut and bring some of these unexplored genes into scientists ’ work ?
Stoeger : This is something we try to answer in some upcoming work by looking historically at cases when people managed to make some genes more popular , [ although ] we realize that it is very rare that people succeed .
But there are a few strategies that might work @ @ @ @ @ @ @ to basically .
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.
take these experiments that survey our genes and actually focus on the new ones .
Another thing to encourage work in this sector [ would be ] initiatives that solicit individual research grants .
Right now , these only include a couple of genes , but there ’ s maybe 10,000 or more genes that would be worthwhile to study .
And then there ’ s one strategy that I personally follow , which is taking some really important biological context that has already been studied a lot @ @ @ @ @ @ @ all of the evidence that ’ s out there and focusing on these genes that have been overlooked but have some mounting evidence that they ’ re important .
TS : You said that if you look in history , there are examples of genes becoming more popular .
Do you have an example of that that comes to mind ?
Stoeger : There is a gene called C9orf72 that is now one of the most popular genes of the last 10 years .
A group [ carried out ] genome-wide association studies @ @ @ @ @ @ @ and different mutations in the human genome .
They found that mutations in this gene were associated with [ dementia and amyotrophic lateral sclerosis ( ALS ) ] .
People didn ’ t expect this gene to be linked to these diseases , but all of a sudden people showed that this gene alone was actually better at explaining which patients would suffer from the diseases than any other gene that had already been studied .
Editor ’ s note : The interview was edited for brevity .

ABOVE: © ISTOCK.COM, THEASIS
Scientists have identified more than 2,000 human genes linked to COVID-19, yet the bulk of the published literature is dominated by only a small subset of them, a fact that may be limiting progress in the fight against the pandemic.
A team at Northwestern University, led by data scientist Thomas Stoeger, had previously shown that scientists tend to focus on a handful of genes—specifically, less than 20 percent of all genes in the human genome accounted for more than 90 percent of the publications they analyzed. Prior to the Human Genome Project, scientists had an incomplete view of the full suite of human genes and relied more heavily on those that had analogs in model organisms or were easier to study using knockout experiments. The advent of modern sequencing technology—including complementary tools such as CRISPR, mass spectrometry, and RNA-based approaches—has broadened what researchers know, but it seems that scientists are still holding to old patterns.
Thomas Stoeger Helio Tejedor Navarro
In a study published today (November 24) in eLife, Stoeger and his Northwestern colleague Luís Amaral looked to COVID-19 research to see if scientists were similarly prioritizing certain genes during the pandemic in case reports and research on mechanisms of infection and transmission, diagnostic tools, and treatments. The pair analyzed 10,395 published papers and preprints and compared the genes studied in those publications against a list of genes linked to the virus through genome-wide association studies (GWAS).
As the pandemic has progressed, they found, scientists have become focused on a small subset of genes to the exclusion of others that may also be important. Of the roughly 2,000 genes identified by the GWAS reports, only 611 were included in the literature they scanned. In particular, three genes, which code [KG1] for angiotensin-converting enzyme 2 (ACE2), a receptor the virus uses to enter cells; C-reactive protein, an inflammation marker; and interleukin 6, a signaling molecule involved in inflammatory responses, accounted for 25 percent of the total research. When they compared these COVID-19 papers against a set of roughly 466,000 non–COVID-19 papers from before 2016, Stoeger and Nunes discovered that whether or not the research related to the pandemic, the same types of genes—those advantageous to experimentation—still command the most attention.
The Scientist spoke with Stoeger about how researchers choose which genes to study, what information they could be missing, and ways that research can open up to previously overlooked genes.
The Scientist: In the paper, you mention this historical bias around the genes that scientists choose to focus on, and you talk about how these choices predate the Human Genome Project. Can you describe how people were selecting genes to study prior to the Human Genome Project?
Thomas Stoeger: Science is difficult, and so scientists start with the least difficult research problems. The research questions scientists worked on before the Human Genome Project tended to be on genes which are interesting and very useful to study, but also happened to be easier to study in a few different ways.
One way is that the human genes [they chose] also had related genes in model organisms, such as fruit flies or worms, and the related gene had already been studied. The shortest genes have also been studied much more than others . . . because they’re easier to work with. And there are also some other chemical properties, for instance, the proteins encoded by the genes. When proteins sit on the outside of the cell, for example, it’s easier to access them. All of these things together made experimentation less difficult.
TS: How does this new paper build upon the previous work that you have done looking at this bias in gene choice for research?
Stoeger: It’s our wish to capture all aspects of biology and make them interlinked so that we can compare social questions to questions of chemistry [and] biology. Conceptually, this paper is a little bit different from the last one. The last one was mostly on things that were in the past. Now, we want to know—for something very current where many scientists are all working on the same thing—to what extent [do] we stick to the same past bias or to what extent do we do something new? So maybe the better answer would be for me to say that we want to know if emerging global threats are subjected to the same biases that affect the rest of the medical literature.
TS: Can you tell me a little bit more about LitCovid, the program that you used to identify the genes being studied in COVID-19 research?
Stoeger: I’m a data scientist who tries to integrate many different resources. I’m always particularly thankful when other institutions have already cleaned the data and brought it into a very nice shape.
LitCovid is a curated list of publications that relate to COVID-19 [managed by the National Institutes of Health], and they’ve already computationally tagged individual concepts within those articles. You can imagine it as having all of the abstracts and titles and results, and whenever there is a word linked to a gene there is something inserted into the text that says, “Here is a gene,” and each gene has a unique number. Computationally what they’re doing is using a type of natural language processing to make a model of how language works and making tags that relate to genes or diseases.
Sharing this data very openly allows people like myself to combine it with other data, such as data from the past or data from different experiments, to see how all of these different things relate together.
TS: What kinds of information might we be missing out on by focusing only on this small subset of genes?
Stoeger: The honest answer is that we really don’t know. We don’t know what all of these other genes that pop up in large experiments related to COVID-19 do. Many of the top studied genes in the COVID-19 literature are very important genes and should be studied, but they’re not the full story.
TS: How do scientists break out of this rut and bring some of these unexplored genes into scientists’ work?
Stoeger: This is something we try to answer in some upcoming work by looking historically at cases when people managed to make some genes more popular, [although] we realize that it is very rare that people succeed.
But there are a few strategies that might work better than others. One strategy is to basically . . . take these experiments that survey our genes and actually focus on the new ones. Another thing to encourage work in this sector [would be] initiatives that solicit individual research grants. Right now, these only include a couple of genes, but there’s maybe 10,000 or more genes that would be worthwhile to study. And then there’s one strategy that I personally follow, which is taking some really important biological context that has already been studied a lot, such as aging, and taking all of the evidence that’s out there and focusing on these genes that have been overlooked but have some mounting evidence that they’re important.
TS: You said that if you look in history, there are examples of genes becoming more popular. Do you have an example of that that comes to mind?
Stoeger: There is a gene called C9orf72 that is now one of the most popular genes of the last 10 years. A group [carried out] genome-wide association studies for the association between some neurological diseases and different mutations in the human genome. They found that mutations in this gene were associated with [dementia and amyotrophic lateral sclerosis (ALS)]. People didn’t expect this gene to be linked to these diseases, but all of a sudden people showed that this gene alone was actually better at explaining which patients would suffer from the diseases than any other gene that had already been studied.
T. Stoeger, L.A.N. Amaral, “COVID-19 research risks ignoring important host genes due to pre-established research patterns,” eLife, doi:10.7554/eLife.61981, 2020.
Editor’s note: The interview was edited for brevity.


thescientist--2020-11-24--Paper Recommends Women Avoid Female Mentors, Drawing Outrage

A study published in Nature Communications November 17 has caused an eruption of outrage among scientists .
The study of 3 million mentor-protégé pairs in STEM found that women trainees who coauthored papers with senior women scientists received fewer citations after they became principal investigators than did women trainees who coauthored with senior men .
That gendered pattern is consistent with previous research documenting citation biases in science .
But what caused a firehose of criticism was the conclusion of the paper , in which the authors suggest that the solution to this disparity is that women should avoid female @ @ @ @ @ @ @ .
“ Instead of coming to the conclusion that their data shows the system is biased , they come to the conclusion that women shouldn ’ t be mentors , which is blaming individuals as opposed to blaming a broken system .
That ’ s why I think it ’ s so harmful , ” says Rebecca Barnes , a geoscientist at Colorado College and co-PI of a National Science Foundation grant that supports a mentoring program for women in her field .
Barnes and her colleagues published a 2020 study showing that @ @ @ @ @ @ @ likelihood that women trainees will be retained in geosciences .
For the Nature Communications study , researchers analyzed a dataset of 215 million scientists and 222 million papers .
They used a computer program to infer the gender of scientists based on their names and designated them as junior or senior scientists ( junior scientists were defined as scientists in the first seven years since their first academic publication ; senior scientists were beyond that ) .
Mentorship was defined by authorship patterns : when a junior scientist coauthored a paper with a @ @ @ @ @ @ @ considered a mentor .
In this way , the researchers identified 3 million unique mentor-protégé pairs spanning more than a century .
To probe whether these authorship patterns were a good measure of mentorship , the researchers also sent a survey to 2,000 scientists in the dataset , 167 of whom responded , that confirmed these authorship patterns involved some form of mentorship .
The researchers then measured the standing of mentors by their average number of citations per year before their first publication with the protégé .
Highly cited mentors were called @ @ @ @ @ @ @ paper ’ s authors .
The researchers also calculated the degree to which the mentor was integrated within networks of scientific collaborations ( that is , how much of a “ hub ” each mentor is in a collaboration network ) .
The mentorship outcome was measured as the number of citations of the protégé ’ s publications published beyond the first seven years of their career and without their mentor as a coauthor .
The study ’ s authors found that “ big shot ” mentors ( and “ hub ” mentors @ @ @ @ @ @ @ with a greater number of citations of their protégés post-independence .
The researchers also found that for all trainees , “ having more female mentors is associated with a decrease in the mentorship outcome , and this decrease can reach as high as 35 % , ” they write in their report .
Next , the researchers examined how the mentorship relationship benefited the mentors .
“ The results suggest that , by mentoring female instead of male protégés , the female mentors compromise their gain from mentorship , and suffer on average @ @ @ @ @ @ @ on their mentored papers , ” the researchers write .
Male mentors did not see an effect on their citations related to the gender of their protégés .
Scientists have heavily criticized the study on methodological grounds as well as on the authors ’ interpretations and policy recommendations .
Methodologically , “ the study conflates authorship with mentorship , ” explains Regina Baucom , who studies plant genetics at the University of Michigan .
“ Lots of coauthors do zero mentoring , ” Brian Uzzi , who researches factors that affect women ’ @ @ @ @ @ @ @ the Kellogg School of Management at Northwestern University , writes in an email .
Uzzi and colleagues published a paper in PNAS earlier this year about mentorship and protégé success that found no differences in the success of women scientists who had male versus female mentors .
In that study , the researchers used data on mentors and protégés from the ProQuest PhD Dissertation & Thesis databank , an official record of advisor-student relationships taken from doctoral theses .
They measured several aspects of protégé success , including winning a scientific prize , @ @ @ @ @ @ @ , and a high citation impact score .
“ Our paper contradicts their paper ’ s finding and recommendations that women scientists do better when mentored by men when a woman ’ s actual and known mentors are identified , ” Uzzi writes in an email to The Scientist .
The study ’ s use of algorithms to identify gender based on names is also problematic because it can lead to mistakes , Baucom and others have pointed out .
Roberta Sinatra , a scholar at the IT University of Copenhagen , uses @ @ @ @ @ @ @ , mentorship , and success in science .
She says that the methods used in the study , although flawed , are fairly standard in this field .
The lack of gender information is a limitation of the dataset , but the algorithms are about 80 percent accurate , and questions about gender bias couldn ’ t begin to be addressed without this approach , she says .
She commends the researchers for taking the extra step to do a survey to confirm that the authorship patterns do in fact reflect some measure @ @ @ @ @ @ @ chaperone , ” rather than “ mentor , ” could be a more apt description of that relationship .
Sinatra herself used that term in a 2018 study on publishing in high impact journals because , she says , the authorship patterns don ’ t reveal anything about the quality of mentorship .
“ Overall , it ’ s a very thorough and comprehensive analysis , ” Sinatra says , adding that she felt some of the methodological criticisms were unfair because the approaches are fairly standard in the field known as the @ @ @ @ @ @ @ with critics who say the researchers should have been more careful in their interpretation of the results .
“ The interpretation starts from the idea that scientists have to achieve a higher number of citations .
I think that is not a good starting point , ” she says .
“ The idea that the goal of mentorship is to maximize the impact of citations later in a protégé ’ s career is a very shaky target.
” Sinatra suspects that the fact that female protégés mentored by women experienced less citation impact @ @ @ @ @ @ @ amplification of bias , ” though more analysis would be needed to confirm that .
But she emphasizes that good mentoring isn ’ t just about citations ; for example , the retention of women and underrepresented minorities is an important aspect of good mentorship that is not captured in the analysis .
The researchers did not control for well-documented structural issues and biases that women in science face with respect to hiring , publication , citation , funding , promotion , and more , says Daniel Acuña , who studies decisionmaking related @ @ @ @ @ @ @ funding at Syracuse University , and who was one of the paper ’ s peer reviewers .
“ To me , the paper seems irresponsible to the point of malfeasance , ” Baucom says .
“ The researchers didn ’ t have a control and a treatment group , so they can ’ t assess the reasons why women might not be as highly cited .
To take that and say to young women , ‘ You shouldn ’ t go work with a woman mentor ’ —that , to me , is @ @ @ @ @ @ @ adds that in this moment in particular , when the pandemic has amplified the structural and societal obstacles that women in science are facing , publishing this paper was a mistake .
See “ Gender Gap in Research Output Widens During Pandemic ” In response to an interview request , the authors of the paper , Bedoor AlShebli , Kinga Makovi , and Talal Rahwan of the Computational Social Science Lab at New York University Abu Dhabi , write in an emailed statement : “ In our paper , we highlight that the @ @ @ @ @ @ @ the achievement of at least two objectives : retaining women in scientific careers—for which female mentors are indispensable , as explicitly mentioned in our paper—and maximizing women ’ s long-term impact in the academy .
As we conclude : ‘ the goal of gender equity in science , regardless of the objective targeted , can not , and should not be shouldered by senior female scientists alone , rather , it should be embraced by the scientific community as a whole.
’ ” In an open letter to the editor of Nature Communications @ @ @ @ @ @ @ HHMI investigator at the Rockefeller University , argues that the paper should be retracted .
“ The conclusions reached by the authors that being mentored by a female scientist is detrimental to career outcomes of young scientists , particularly female scientists , are based on flawed assumptions and flawed analysis .
I find it deeply discouraging that this message—avoid a female mentor or your career will suffer—is being amplified by your journal , ” she writes .
In response to these criticisms , the journal is reviewing the work .
“ We believe @ @ @ @ @ @ @ of science , and welcome the review launched by the Editor in Chief of Nature Communications , which we think will lead to a thorough and rigorous discussion of the work and its complex implications , ” the study ’ s authors write in their statement to The Scientist .
One thing both the authors of the paper and its critics can agree on is that the systemic biases against women in science will require systemic solutions .
And one way that this bias can begin to be addressed , Sinatra says , @ @ @ @ @ @ @ hiring , and promotion decisions to take the citation index with a grain of salt .
In short , because it is biased , “ we can not trust this measure .
We need to make an active effort to not focus too much on this number or make choices based on optimizing this number , ” she says .
Correction ( November 24 ) : Roberta Sinatra ’ s affiliation is IT University of Copenhagen , not the University of Copenhagen as originally stated .
The Scientist regrets the error .

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Update (December 21): The authors retracted the paper today after three experts reviewed the study post-publication and agreed with criticisms about the use of coauthorship as a proxy for mentorship. “Although we believe that all the key findings of the paper with regards to co-authorship between junior and senior researchers are still valid, given the issues identified by reviewers about the validation of key measures, we have concluded that the most appropriate course of action is to retract the Article,” the authors write in the retraction notice, adding that they regret the pain the paper caused among members of the scientific community.
A study published in Nature Communications November 17 has caused an eruption of outrage among scientists. The study of 3 million mentor-protégé pairs in STEM found that women trainees who coauthored papers with senior women scientists received fewer citations after they became principal investigators than did women trainees who coauthored with senior men. That gendered pattern is consistent with previous research documenting citation biases in science. But what caused a firehose of criticism was the conclusion of the paper, in which the authors suggest that the solution to this disparity is that women should avoid female mentors, thus perpetuating an existing bias.
“Instead of coming to the conclusion that their data shows the system is biased, they come to the conclusion that women shouldn’t be mentors, which is blaming individuals as opposed to blaming a broken system. That’s why I think it’s so harmful,” says Rebecca Barnes, a geoscientist at Colorado College and co-PI of a National Science Foundation grant that supports a mentoring program for women in her field. Barnes and her colleagues published a 2020 study showing that exposure to women role models increases the likelihood that women trainees will be retained in geosciences.
For the Nature Communications study, researchers analyzed a dataset of 215 million scientists and 222 million papers. They used a computer program to infer the gender of scientists based on their names and designated them as junior or senior scientists (junior scientists were defined as scientists in the first seven years since their first academic publication; senior scientists were beyond that). Mentorship was defined by authorship patterns: when a junior scientist coauthored a paper with a senior scientist, the senior scientist was considered a mentor. In this way, the researchers identified 3 million unique mentor-protégé pairs spanning more than a century.
The idea that the goal of mentorship is to maximize the impact of citations later in a protégé’s career is a very shaky target. —Roberta Sinatra, IT University of Copenhagen
To probe whether these authorship patterns were a good measure of mentorship, the researchers also sent a survey to 2,000 scientists in the dataset, 167 of whom responded, that confirmed these authorship patterns involved some form of mentorship.
The researchers then measured the standing of mentors by their average number of citations per year before their first publication with the protégé. Highly cited mentors were called “big shot” mentors by the paper’s authors. The researchers also calculated the degree to which the mentor was integrated within networks of scientific collaborations (that is, how much of a “hub” each mentor is in a collaboration network). The mentorship outcome was measured as the number of citations of the protégé’s publications published beyond the first seven years of their career and without their mentor as a coauthor.
The study’s authors found that “big shot” mentors (and “hub” mentors to a lesser degree) were associated with a greater number of citations of their protégés post-independence. The researchers also found that for all trainees, “having more female mentors is associated with a decrease in the mentorship outcome, and this decrease can reach as high as 35%,” they write in their report.
Next, the researchers examined how the mentorship relationship benefited the mentors. “The results suggest that, by mentoring female instead of male protégés, the female mentors compromise their gain from mentorship, and suffer on average a loss of 18% in citations on their mentored papers,” the researchers write. Male mentors did not see an effect on their citations related to the gender of their protégés.
Scientists have heavily criticized the study on methodological grounds as well as on the authors’ interpretations and policy recommendations. Methodologically, “the study conflates authorship with mentorship,” explains Regina Baucom, who studies plant genetics at the University of Michigan.
“Lots of coauthors do zero mentoring,” Brian Uzzi, who researches factors that affect women’s success in science and business at the Kellogg School of Management at Northwestern University, writes in an email.
Uzzi and colleagues published a paper in PNAS earlier this year about mentorship and protégé success that found no differences in the success of women scientists who had male versus female mentors. In that study, the researchers used data on mentors and protégés from the ProQuest PhD Dissertation & Thesis databank, an official record of advisor-student relationships taken from doctoral theses. They measured several aspects of protégé success, including winning a scientific prize, election to the National Academy of Sciences, and a high citation impact score. “Our paper contradicts their paper’s finding and recommendations that women scientists do better when mentored by men when a woman’s actual and known mentors are identified,” Uzzi writes in an email to The Scientist.
The study’s use of algorithms to identify gender based on names is also problematic because it can lead to mistakes, Baucom and others have pointed out.
Roberta Sinatra, a scholar at the IT University of Copenhagen, uses big data to study publication, citation, mentorship, and success in science. She says that the methods used in the study, although flawed, are fairly standard in this field. The lack of gender information is a limitation of the dataset, but the algorithms are about 80 percent accurate, and questions about gender bias couldn’t begin to be addressed without this approach, she says. She commends the researchers for taking the extra step to do a survey to confirm that the authorship patterns do in fact reflect some measure of mentorship, but suggests that “chaperone,” rather than “mentor,” could be a more apt description of that relationship. Sinatra herself used that term in a 2018 study on publishing in high impact journals because, she says, the authorship patterns don’t reveal anything about the quality of mentorship.
Citations as success
“Overall, it’s a very thorough and comprehensive analysis,” Sinatra says, adding that she felt some of the methodological criticisms were unfair because the approaches are fairly standard in the field known as the science of science. But she agrees with critics who say the researchers should have been more careful in their interpretation of the results. “The interpretation starts from the idea that scientists have to achieve a higher number of citations. I think that is not a good starting point,” she says. “The idea that the goal of mentorship is to maximize the impact of citations later in a protégé’s career is a very shaky target.”
Sinatra suspects that the fact that female protégés mentored by women experienced less citation impact later is likely due to an “amplification of bias,” though more analysis would be needed to confirm that. But she emphasizes that good mentoring isn’t just about citations; for example, the retention of women and underrepresented minorities is an important aspect of good mentorship that is not captured in the analysis.
The researchers did not control for well-documented structural issues and biases that women in science face with respect to hiring, publication, citation, funding, promotion, and more, says Daniel Acuña, who studies decisionmaking related to scientific publication, collaboration, and funding at Syracuse University, and who was one of the paper’s peer reviewers.
“To me, the paper seems irresponsible to the point of malfeasance,” Baucom says. “The researchers didn’t have a control and a treatment group, so they can’t assess the reasons why women might not be as highly cited. To take that and say to young women, ‘You shouldn’t go work with a woman mentor’—that, to me, is malfeasance,” she says. She adds that in this moment in particular, when the pandemic has amplified the structural and societal obstacles that women in science are facing, publishing this paper was a mistake.
See “Gender Gap in Research Output Widens During Pandemic”
In response to an interview request, the authors of the paper, Bedoor AlShebli, Kinga Makovi, and Talal Rahwan of the Computational Social Science Lab at New York University Abu Dhabi, write in an emailed statement: “In our paper, we highlight that the elevation of women in science depends on the achievement of at least two objectives: retaining women in scientific careers—for which female mentors are indispensable, as explicitly mentioned in our paper—and maximizing women’s long-term impact in the academy. As we conclude: ‘the goal of gender equity in science, regardless of the objective targeted, cannot, and should not be shouldered by senior female scientists alone, rather, it should be embraced by the scientific community as a whole.’”
In an open letter to the editor of Nature Communications, Leslie Vosshall, a neurogeneticist and HHMI investigator at the Rockefeller University, argues that the paper should be retracted. “The conclusions reached by the authors that being mentored by a female scientist is detrimental to career outcomes of young scientists, particularly female scientists, are based on flawed assumptions and flawed analysis. I find it deeply discouraging that this message—avoid a female mentor or your career will suffer—is being amplified by your journal,” she writes.
In response to these criticisms, the journal is reviewing the work.
“We believe that free inquiry and debate are engines of science, and welcome the review launched by the Editor in Chief of Nature Communications, which we think will lead to a thorough and rigorous discussion of the work and its complex implications,” the study’s authors write in their statement to The Scientist.
One thing both the authors of the paper and its critics can agree on is that the systemic biases against women in science will require systemic solutions. And one way that this bias can begin to be addressed, Sinatra says, is for committees involved in funding, hiring, and promotion decisions to take the citation index with a grain of salt. In short, because it is biased, “we cannot trust this measure. We need to make an active effort to not focus too much on this number or make choices based on optimizing this number,” she says.
Correction (November 24): Roberta Sinatra’s affiliation is IT University of Copenhagen, not the University of Copenhagen as originally stated. The Scientist regrets the error.


thescientist--2020-11-24--Q&A: Science Has Been Resilient During Pandemic, Survey Finds

Scientists , like everyone else , have had to adapt creatively to the pandemic this year—whether by making labs out of their laundry rooms or quickly pivoting their research to SARS-CoV-2 and the disease it causes .
In late October , journal publisher Frontiers reported results from a survey that asked those researchers how the pandemic has affected their lives .
Based on data collected in May and June from 25,307 participants worldwide , the findings offer insight into scientists ’ working conditions in the time of COVID-19 , their attitudes to how scientific findings should be shared , and @ @ @ @ @ @ @ The Scientist spoke to Frontiers ’ s marketing and communications director Chantelle Rijs , who led the study along with executive editor Frederick Fenter , to learn more about the survey and its findings .
TS : Why did Frontiers want to do this survey of researchers ?
Chantelle Rijs : We are all very passionate about science and we are very passionate about the role that science plays in society .
.
.
.
It ’ s the science that ’ s going to help us get out of this crisis .
@ @ @ @ @ @ @ give our community , the scientists , a voice during this incredibly challenging time , especially when they are under such extraordinary pressure to provide answers .
TS : Can you tell me about who took part in your survey ?
CR : The participants are all members of the Frontiers community .
Our community is made up of active researchers who have either published their research with us or sit on one of our editorial boards as an editor or a reviewer .
A hundred and fifty-two countries are represented in the @ @ @ @ @ @ @ , not necessarily the wider scientific community .
We have around six hundred thousand authors and one hundred thousand editors and reviewers .
The majority of them come from the US and Europe , so we were not surprised to see the highest number of responses coming from those particular regions .
.
.
.
In total , we had over twenty-five thousand academics who participated .
From what we can tell , this is one of the largest academic surveys that has been conducted .
I think this is indicative of the @ @ @ @ @ @ @ be heard , and we were very happy to be able to provide them that platform .
TS : What did you learn about how researchers ’ day-to-day lives have been affected this year ?
CR : So , twenty percent of researchers reported that their worlds had completely changed and that they are now no longer able to do their work .
South American countries appeared to be the hardest hit by this—almost a third of respondents in Argentina , Chile , Brazil all said they were no longer able to perform @ @ @ @ @ @ @ this massive disruption to our lives , the majority of the research community has been resolute .
We ’ ve had seventy percent of researchers saying they ’ re able to continue with their research , even if from home , and ten percent saying that they ’ ve been completely unaffected by the pandemic .
Writing papers for publication was the most common task—also unsurprising , considering they ’ re now out of the lab and in their home offices .
It ’ s something that we felt at Frontiers as well—we @ @ @ @ @ @ @ over this time .
But I think more importantly , it really was very encouraging for us , and it gave us a sense of hope that the research community is able to remain resilient during times like this , especially with new waves of COVID sweeping across the world right now .
TS : That increase in papers you mentioned—was it on a particular topic ?
CR : It was on coronavirus .
We had around six thousand submissions on COVID papers alone .
TS : There ’ s been a lot @ @ @ @ @ @ @ did your survey reveal about scientists ’ attitudes towards data sharing and open science , and how those attitudes might have changed this year ?
CR : I think that the pandemic has encouraged many to reconsider how they share their work , with researchers saying that they are now more likely to publish open access , they are more likely to share their data , and they are more likely to start using something like a preprint server as a result of COVID-19 .
We saw that PhD students and medical professionals @ @ @ @ @ @ @ biggest supporters of open science and data sharing .
But we also saw other publishers make all of their coronavirus research open and accessible as soon as the pandemic hit .
So our question is : What about their oncology research , or their research into dementia or Alzheimer ’ s ?
It ’ s very obvious to us that all research needs to be open access , not just coronavirus research .
It will be interesting to see whether these paywalls are reinstated in time , or whether they ’ ll decide @ @ @ @ @ @ @ TS : A few parts of the survey asked researchers to think about what ’ s going to happen later in the pandemic and after the pandemic .
What were some of the biggest concerns that scientists had for the future ?
CR : The results showed that researchers are pragmatically considering how to prepare for and mitigate future crises .
Their biggest concern is the threat of a future pandemic—again , unsurprising given that the questions were asked right in the midst of the first wave .
They warned about the danger @ @ @ @ @ @ @ bacterial diseases arising from antibiotic resistance .
Here , they stressed the importance of learning from our current situation to prepare for any future threats that might arise .
The second-biggest concern was climate change .
And here they drew parallels between the immediate actions taken to mitigate COVID-19 and the kind of action needed to tackle environmental threats .
There ’ s concern that funding is being redirected away from their areas of research .
One of my colleagues commented that scientists are always going to say they ’ re worried about @ @ @ @ @ @ @ , there is concern about the covidization of research funding—that it all gets funneled into COVID research at the neglect and at the expense of other key areas .
TS : These data were collected in May and June .
Are there things you expect to have changed since then , and are you collecting more data ?
CR : We ’ re definitely considering doing another one next year .
Just this week alone , there are lots of reports coming out .
.
.
around vaccine development .
The efficacy of @ @ @ @ @ @ @ extent how we ’ re all living and working , and the concerns that we have , in the future .
It will be very interesting to see where we are in six to twelve months ’ time , and if we still have those same concerns .
I ’ m not sure we ’ ll do such a big survey again .
We had around twenty questions and we also asked them information about their field of study , location , et cetera .
.
.
.
Maybe a smaller subset of @ @ @ @ @ @ @ rather than a big extensive survey like the one we just conducted .
It would allow us to get the results out quicker as well—to collate twenty-five thousand survey results is very time intensive .
Editor ’ s note : The interview was edited for brevity .

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YORKFOTO
Scientists, like everyone else, have had to adapt creatively to the pandemic this year—whether by making labs out of their laundry rooms or quickly pivoting their research to SARS-CoV-2 and the disease it causes. In late October, journal publisher Frontiers reported results from a survey that asked those researchers how the pandemic has affected their lives. Based on data collected in May and June from 25,307 participants worldwide, the findings offer insight into scientists’ working conditions in the time of COVID-19, their attitudes to how scientific findings should be shared, and their biggest concerns for the future.
The Scientist spoke to Frontiers’s marketing and communications director Chantelle Rijs, who led the study along with executive editor Frederick Fenter, to learn more about the survey and its findings.
TS: Why did Frontiers want to do this survey of researchers?
Chantelle Rijs: We are all very passionate about science and we are very passionate about the role that science plays in society. . . . It’s the science that’s going to help us get out of this crisis. So it was imperative for us to give our community, the scientists, a voice during this incredibly challenging time, especially when they are under such extraordinary pressure to provide answers.
Twenty percent of researchers reported that their worlds had completely changed and that they are now no longer able to do their work.
TS: Can you tell me about who took part in your survey?
CR: The participants are all members of the Frontiers community. Our community is made up of active researchers who have either published their research with us or sit on one of our editorial boards as an editor or a reviewer. A hundred and fifty-two countries are represented in the study, but it represents our network, not necessarily the wider scientific community.
We have around six hundred thousand authors and one hundred thousand editors and reviewers. The majority of them come from the US and Europe, so we were not surprised to see the highest number of responses coming from those particular regions. . . . In total, we had over twenty-five thousand academics who participated. From what we can tell, this is one of the largest academic surveys that has been conducted. I think this is indicative of the fact that the scientists themselves want to be heard, and we were very happy to be able to provide them that platform.
TS: What did you learn about how researchers’ day-to-day lives have been affected this year?
CR: So, twenty percent of researchers reported that their worlds had completely changed and that they are now no longer able to do their work. South American countries appeared to be the hardest hit by this—almost a third of respondents in Argentina, Chile, Brazil all said they were no longer able to perform their job function.
However, despite this massive disruption to our lives, the majority of the research community has been resolute. We’ve had seventy percent of researchers saying they’re able to continue with their research, even if from home, and ten percent saying that they’ve been completely unaffected by the pandemic.
Writing papers for publication was the most common task—also unsurprising, considering they’re now out of the lab and in their home offices. It’s something that we felt at Frontiers as well—we saw a sudden increase in manuscript submissions over this time.
But I think more importantly, it really was very encouraging for us, and it gave us a sense of hope that the research community is able to remain resilient during times like this, especially with new waves of COVID sweeping across the world right now.
The percentage of respondents (in a sampling of countries) who responded that they were “no longer able to perform my work, or my role has changed completely” in answer to the question, “How has the COVID-19 pandemic affected the way you work?” DATA SOURCE: FRONTIERS
TS: That increase in papers you mentioned—was it on a particular topic?
CR: It was on coronavirus. We had around six thousand submissions on COVID papers alone.
TS: There’s been a lot of debate about open science. What did your survey reveal about scientists’ attitudes towards data sharing and open science, and how those attitudes might have changed this year?
CR: I think that the pandemic has encouraged many to reconsider how they share their work, with researchers saying that they are now more likely to publish open access, they are more likely to share their data, and they are more likely to start using something like a preprint server as a result of COVID-19. We saw that PhD students and medical professionals were the two groups who were the biggest supporters of open science and data sharing.
There is concern about the covidization of research funding—that it all gets funneled into COVID research at the neglect and at the expense of other key areas.
But we also saw other publishers make all of their coronavirus research open and accessible as soon as the pandemic hit. So our question is: What about their oncology research, or their research into dementia or Alzheimer’s? It’s very obvious to us that all research needs to be open access, not just coronavirus research. It will be interesting to see whether these paywalls are reinstated in time, or whether they’ll decide to unlock research in other areas.
See “Journals Open Access to Coronavirus Research”
TS: A few parts of the survey asked researchers to think about what’s going to happen later in the pandemic and after the pandemic. What were some of the biggest concerns that scientists had for the future?
CR: The results showed that researchers are pragmatically considering how to prepare for and mitigate future crises. Their biggest concern is the threat of a future pandemic—again, unsurprising given that the questions were asked right in the midst of the first wave. They warned about the danger of new viruses, vector-borne diseases, bacterial diseases arising from antibiotic resistance. Here, they stressed the importance of learning from our current situation to prepare for any future threats that might arise.
The second-biggest concern was climate change. And here they drew parallels between the immediate actions taken to mitigate COVID-19 and the kind of action needed to tackle environmental threats.
There’s concern that funding is being redirected away from their areas of research. One of my colleagues commented that scientists are always going to say they’re worried about funding . . . . But yes, there is concern about the covidization of research funding—that it all gets funneled into COVID research at the neglect and at the expense of other key areas.
Percentages of respondents who mentioned particular subjects in response to the question, “What future threats could be prevented if we prepare for them properly?” Frontiers analyzed text responses using an algorithm that identified keywords and themes; each person’s response could be categorized in more than one theme. DATA SOURCE: FRONTIERS
TS: These data were collected in May and June. Are there things you expect to have changed since then, and are you collecting more data?
CR: We’re definitely considering doing another one next year. Just this week alone, there are lots of reports coming out . . . around vaccine development. The efficacy of those vaccines will dictate to a certain extent how we’re all living and working, and the concerns that we have, in the future. It will be very interesting to see where we are in six to twelve months’ time, and if we still have those same concerns.
I’m not sure we’ll do such a big survey again. We had around twenty questions and we also asked them information about their field of study, location, et cetera. . . . Maybe a smaller subset of that, focusing on key areas, rather than a big extensive survey like the one we just conducted. It would allow us to get the results out quicker as well—to collate twenty-five thousand survey results is very time intensive.
Editor’s note: The interview was edited for brevity.