thescientist--2020-12-01--Action at a Distance, Circa Early 1950s

Action at a Distance, Circa Early 1950s

What do nerves need in order to grow ?
That question first caught Rita Levi-Montalcini ’ s attention in the 1930s , when she came across a recent paper by embryologist Viktor Hamburger .
After observing that clipping the wing bud off chicken embryos stunted the growth of spinal nerves and ganglia on the side of the body with the excision , Hamburger reported that signals from the limb drove the growth and differentiation of immature cells in the central nervous system .
Levi-Montalcini was intrigued .
But after repeating the embryo experiments and finding that the chick ’ s @ @ @ @ @ @ @ and died later—just before reaching their target tissue—she came to a different conclusion .
Rather than failing to initiate nerve growth , she hypothesized , the animals were unable to sustain the growing cells , causing a degenerative process that limited their proliferation .
Levi-Montalcini began these experiments at the University of Turin in Italy , but as a Jewish scientist , she was forced to leave in 1938 when Mussolini ’ s Fascist government made it illegal for her to work at state universities .
She continued the work from a secret @ @ @ @ @ @ @ the end of World War II .
Levi-Montalcini sent reports to her former advisor , histologist Giuseppe Levi ( no relation to Levi-Montalcini ) , then in Belgium , who published their coauthored manuscripts in academic journals .
In 1946 , Hamburger invited Levi-Montalcini to his lab at Washington University in St. Louis .
Together , they found that many nerve cells die during normal development , and that limb amputations heighten this loss .
Soon after , Levi-Montalcini followed up on the findings of Hamburger ’ s former graduate student Elmer Bueker @ @ @ @ @ @ @ the developing limb , a rapidly growing malignant tumor could also promote the growth of nerve cells in chicken embryos .
Levi-Montalcini transplanted tumors onto the membrane around an embryo , where they were only connected to the developing animal by a common blood supply , and demonstrated that the tumors could still encourage neural growth .
It seemed there was a diffusible agent that was influencing nervous system development .
In the early 1950s , Levi-Montalcini began collaborating with biochemist Stanley Cohen , who had just joined Hamburger ’ s lab .
@ @ @ @ @ @ @ molecule , nerve growth factor ( NGF ) , which turned out to be crucial for the development and survival of cells in the nervous system .
Cohen later identified another factor , epidermal growth factor ( EGF ) , which stimulates the growth of epithelial cells .
And in 1986 , Levi-Montalcini and Cohen shared the Nobel Prize in Physiology or Medicine for their discoveries of NGF and EGF , respectively .
The discovery of these first growth factors was a “ breakthrough in the field of extracellular messengers , ” a @ @ @ @ @ @ @ , says Pietro Calissano , a neuroscientist and vice president of the European Brain Research Institute in Italy , which Levi-Montalcini founded .
“ [ NGF and EGF ] brought to light the existence of an entirely new category of diffusible substances.
” Following the discovery of NGF , Levi-Montalcini spent much of the rest of her career investigating the role of the growth factor in the developing nervous system .
Before passing away in 2012 at the age of 103 , she also penned several books and set up a foundation to @ @ @ @ @ @ @ students seeking higher education .
Calissano , who worked with Levi-Montalcini for more than 40 years , remembers her as “ a brilliant scientist and charming woman who liked to approach research with imagination .
”

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What do nerves need in order to grow? That question first caught Rita Levi-Montalcini’s attention in the 1930s, when she came across a recent paper by embryologist Viktor Hamburger. After observing that clipping the wing bud off chicken embryos stunted the growth of spinal nerves and ganglia on the side of the body with the excision, Hamburger reported that signals from the limb drove the growth and differentiation of immature cells in the central nervous system. Levi-Montalcini was intrigued. But after repeating the embryo experiments and finding that the chick’s nerve cells continued to develop after amputation and died later—just before reaching their target tissue—she came to a different conclusion. Rather than failing to initiate nerve growth, she hypothesized, the animals were unable to sustain the growing cells, causing a degenerative process that limited their proliferation.
Levi-Montalcini began these experiments at the University of Turin in Italy, but as a Jewish scientist, she was forced to leave in 1938 when Mussolini’s Fascist government made it illegal for her to work at state universities. She continued the work from a secret, makeshift laboratory in her bedroom until the end of World War II.
VENOMOUS GROWTH: Rita Levi-Montalcini and Stanley Cohen found that when nerve tissue from chicken embryos is cultured alongside snake venom, a rich source of nerve growth factor (NGF), it grows a dense halo of nerve fibers (right). Without NGF (left), fewer nerve fibers develop, and those that do grow are smaller. PNAS, 42:571–74, 1956
Levi-Montalcini sent reports to her former advisor, histologist Giuseppe Levi (no relation to Levi-Montalcini), then in Belgium, who published their coauthored manuscripts in academic journals. In 1946, Hamburger invited Levi-Montalcini to his lab at Washington University in St. Louis. Together, they found that many nerve cells die during normal development, and that limb amputations heighten this loss. Soon after, Levi-Montalcini followed up on the findings of Hamburger’s former graduate student Elmer Bueker, who had observed that, like the developing limb, a rapidly growing malignant tumor could also promote the growth of nerve cells in chicken embryos. Levi-Montalcini transplanted tumors onto the membrane around an embryo, where they were only connected to the developing animal by a common blood supply, and demonstrated that the tumors could still encourage neural growth. It seemed there was a diffusible agent that was influencing nervous system development.
In the early 1950s, Levi-Montalcini began collaborating with biochemist Stanley Cohen, who had just joined Hamburger’s lab. The pair isolated and characterized the mystery molecule, nerve growth factor (NGF), which turned out to be crucial for the development and survival of cells in the nervous system. Cohen later identified another factor, epidermal growth factor (EGF), which stimulates the growth of epithelial cells. And in 1986, Levi-Montalcini and Cohen shared the Nobel Prize in Physiology or Medicine for their discoveries of NGF and EGF, respectively. The discovery of these first growth factors was a “breakthrough in the field of extracellular messengers,” a category that also includes vitamins and hormones, says Pietro Calissano, a neuroscientist and vice president of the European Brain Research Institute in Italy, which Levi-Montalcini founded. “[NGF and EGF] brought to light the existence of an entirely new category of diffusible substances.”
Following the discovery of NGF, Levi-Montalcini spent much of the rest of her career investigating the role of the growth factor in the developing nervous system. Before passing away in 2012 at the age of 103, she also penned several books and set up a foundation to provide guidance and financial support to young students seeking higher education. Calissano, who worked with Levi-Montalcini for more than 40 years, remembers her as “a brilliant scientist and charming woman who liked to approach research with imagination.”


thescientist--2020-12-01--Immune Genes Protect Cells from Ebola Virus and SARS-CoV-2

The paper A. Bruchez et al.
, “ MHC class II transactivator CIITA induces cell resistance to Ebola virus and SARS-like coronaviruses , ” Science , 370:241–47 , 2020 .
Earlier this year , immunologist Adam Lacy-Hulbert of the Benaroya Research Institute in Seattle and his former postdoc Anna Bruchez were writing up their discovery of a previously unknown immune pathway that defends cells against Ebola virus .
Then SARS-CoV-2 hit the US .
The two suspected that the pathway provided broad antiviral defense , so they decided to test it against the novel coronavirus .
In the Ebola experiments @ @ @ @ @ @ @ colleagues had been using a genetic screen called transposon-mediated gene activation to search for natural antiviral mechanisms within cultured human bone cancer cells .
Transposons , mobile genetic elements found throughout the genome , can be added to cells to knock out genes they randomly insert into .
The team had integrated a promoter sequence into the transposons so that , in addition to knocking out some genes , they would turn other genes on .
After adding these transposons to flasks of human cells , Bruchez introduced viruses engineered to express an @ @ @ @ @ @ @ cells .
The team genotyped the few cells that remained and discovered two genes that were crucial to the cells ’ survival : NPC1 and CIITA .
NPC1 encodes the receptor that Ebola virus binds to , but CIITA was more mysterious .
It encodes a transcription factor that regulates major histocompatibility complex ( MHC ) genes , which code for the cell surface proteins that present foreign substances to adaptive immune cells .
But the team ’ s cultures lacked adaptive immune cells ( such as T cells ) , suggesting a @ @ @ @ @ @ @ .
To find out what it was , the team knocked down each of the genes that CIITA regulates , and found one , CD74 ( which encodes part of the MHC ) , that was key to cell survival .
One isoform in particular , p41 , could keep CD74 knockout cells alive in the face of the virus with the Ebola glycoprotein .
Electron microscopy showed that , in cells expressing p41 , the glycoprotein remained trapped inside the endosomes that housed the engineered viruses after they were internalized by the @ @ @ @ @ @ @ proteases called cathepsins , preventing the enzymes from cleaving the Ebola glycoprotein , thus stopping the fusion of the virus with the endosome and the release of the viral genome into the cell , the team demonstrated .
The group found that p41 inhibited entry of SARS-CoV-2 into the cells as well .
Lacy-Hulbert suggests that this pathway could trigger broad resistance to viruses and that this “ might have been CIITA and CD74 ’ s original role .
Then that activity got co-opted into the adaptive immune system , which evolved later.
@ @ @ @ @ @ @ University says the study makes a strong case that CIITA and CD74 mitigate Ebola infection in vitro via cathepsins .
But he notes that a 2012 study in mice showed that knocking out cathepsins does not prevent Ebola infection , and he questions the importance of the CIITA/CD74 pathway as a primary antiviral mechanism in animals and humans .
In addition , SARS-CoV-2 does not depend solely on cathepsins to infect cells , he notes .
But Lacy-Hulbert says it ’ s likely the viruses use different proteases for entry depending on the @ @ @ @ @ @ @ and it ’ s possible that CIITA and CD74 p41 can block other proteases as well .
He adds , “ the pathways we have identified are likely to be important in animals and humans , but may need to act in combination with other pathways .
”

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EDITOR’S CHOICE IN IMMUNOLOGY
The paper
A. Bruchez et al., “MHC class II transactivator CIITA induces cell resistance to Ebola virus and SARS-like coronaviruses,” Science, 370:241–47, 2020.
Earlier this year, immunologist Adam Lacy-Hulbert of the Benaroya Research Institute in Seattle and his former postdoc Anna Bruchez were writing up their discovery of a previously unknown immune pathway that defends cells against Ebola virus. Then SARS-CoV-2 hit the US. The two suspected that the pathway provided broad antiviral defense, so they decided to test it against the novel coronavirus.
In the Ebola experiments, Lacy-Hulbert, Bruchez, and their colleagues had been using a genetic screen called transposon-mediated gene activation to search for natural antiviral mechanisms within cultured human bone cancer cells. Transposons, mobile genetic elements found throughout the genome, can be added to cells to knock out genes they randomly insert into. The team had integrated a promoter sequence into the transposons so that, in addition to knocking out some genes, they would turn other genes on. After adding these transposons to flasks of human cells, Bruchez introduced viruses engineered to express an Ebola glycoprotein, killing most of the cells. The team genotyped the few cells that remained and discovered two genes that were crucial to the cells’ survival: NPC1 and CIITA.
PDF TRAP AND KILL: Overexpressing the transcription factor CIITA in cultured human cells turns on a gene called CD74, producing the protein p41, which binds to cathepsin proteases in the endosome (left). When the cells are exposed to an Ebola-mimicking virus, the p41-bound cathepsins are unable to cleave off the virus’s glycoprotein, stopping it from fusing with the membrane and thus trapping it inside the endosome. Later, the virus is likely brought to lysosomes and destroyed (not pictured). In a cell where CD74 is not overexpressed (right), cathepsins cleave the virus’s glycoproteins, enabling it to fuse with the side of the endosome and release its genetic material into the cytosol. WEB © KIMBERLY BATTISTA
NPC1 encodes the receptor that Ebola virus binds to, but CIITA was more mysterious. It encodes a transcription factor that regulates major histocompatibility complex (MHC) genes, which code for the cell surface proteins that present foreign substances to adaptive immune cells. But the team’s cultures lacked adaptive immune cells (such as T cells), suggesting a more primitive type of defense was occurring. To find out what it was, the team knocked down each of the genes that CIITA regulates, and found one, CD74 (which encodes part of the MHC), that was key to cell survival. One isoform in particular, p41, could keep CD74 knockout cells alive in the face of the virus with the Ebola glycoprotein. Electron microscopy showed that, in cells expressing p41, the glycoprotein remained trapped inside the endosomes that housed the engineered viruses after they were internalized by the cell. The p41 protein binds to proteases called cathepsins, preventing the enzymes from cleaving the Ebola glycoprotein, thus stopping the fusion of the virus with the endosome and the release of the viral genome into the cell, the team demonstrated.
The group found that p41 inhibited entry of SARS-CoV-2 into the cells as well. Lacy-Hulbert suggests that this pathway could trigger broad resistance to viruses and that this “might have been CIITA and CD74’s original role. Then that activity got co-opted into the adaptive immune system, which evolved later.”
Virologist Yong-Hui Zheng of Michigan State University says the study makes a strong case that CIITA and CD74 mitigate Ebola infection in vitro via cathepsins. But he notes that a 2012 study in mice showed that knocking out cathepsins does not prevent Ebola infection, and he questions the importance of the CIITA/CD74 pathway as a primary antiviral mechanism in animals and humans. In addition, SARS-CoV-2 does not depend solely on cathepsins to infect cells, he notes. But Lacy-Hulbert says it’s likely the viruses use different proteases for entry depending on the cell type they’re infecting, and it’s possible that CIITA and CD74 p41 can block other proteases as well. He adds, “the pathways we have identified are likely to be important in animals and humans, but may need to act in combination with other pathways.”


Ten Minute Sabbatical

1 .
Like muscle tissue with sarcomeres 6 .
Sir Humphry who isolated sodium 8 .
Unit of temperature named @ @ @ @ @ Proteins that form microfilaments 10 .
Virus that infects prokaryotes 11 .
Slender projection of @ @ @ @ @ up , as chromosomes during meiosis 16 .
Neurons in the cerebellum with many dendrites @ @ @ @ @ 19 .
Vessel typically carrying oxygenated blood 20 .
Prove Darwin right ?
21 .
@ @ @ @ @ germ layer of an embryo

ACROSS 1. Like muscle tissue with sarcomeres
6. Sir Humphry who isolated sodium
8. Unit of temperature named for William Thomson
9. Proteins that form microfilaments
10. Virus that infects prokaryotes
11. Slender projection of a neuron
12. Match up, as chromosomes during meiosis
16. Neurons in the cerebellum with many dendrites (2 wds.)
19. Vessel typically carrying oxygenated blood
20. Prove Darwin right?
21. Newtonian trio
22. Outermost germ layer of an embryo


thescientist--2020-12-01--Nutrition Researchers Can Determine What You've Been Eating

Between 2013 and 2014 , 19 people were voluntarily locked in a clinic for days at a time—not once , but on four separate occasions .
They were fed a different , strict diet on each of their three-day-long visits , and were forbidden to exercise .
Computer access and visitation were allowed , so long as guests didn ’ t smuggle in snacks .
Subjects turned over all their urine , from morning , afternoon , and night , to researchers .
These participants temporarily sacrificed their freedom to help dietician Gary Frost and colleagues at Imperial College London @ @ @ @ @ @ @ concentrations of metabolites excreted in urine , and thus how urine could serve as an indicator of a person ’ s diet , which in the team ’ s experiment ranged from healthy to gluttonous .
Frost ’ s team anticipated that such metabolomics analyses would provide more-reliable data for nutritionists than the traditional tactic of asking free-roaming subjects what they ’ ve been noshing—an approach that is notorious for its huge error rates .
“ Most people have a really bad memory of what they ’ re eating .
.
.
.
@ @ @ @ @ @ @ forget that they ate a chocolate , ” says David Wishart , a biochemist who works on metabolomics and nutrition at the University of Alberta but was not involved in Frost ’ s study .
On the other hand , he adds , “ blood and urine don ’ t lie.
” Indeed , Frost ’ s team was able to use the volunteers ’ data to turn profiles of metabolites in urine into a single score , which they can now use to make inferences about the diets of people whose meals @ @ @ @ @ @ @ researchers seeking objectivity in nutrition research are identifying metabolites that reveal if a person has consumed a specific food .
The approach is not yet perfected or widespread , and researchers are still working to define the metabolites linked to certain dietary qualities or foods .
But with careful analyses , scientists are beginning to uncover nuanced information about people ’ s diets , such as how much milk and cheese they consume , or what kind of brew coffee drinkers drink .
As the techniques improve and data on diet-metabolite correlations amass @ @ @ @ @ @ @ , which seeks to elucidate links between specific eating habits and disease risk .
Some even see an opportunity to develop personalized nutrition recommendations to help people boost or maintain physical and mental health .
Wishart , for example , is the chief informatics officer at a Vancouver-based company called Molecular You that uses metabolomics and other information to advise customers on eating habits to improve their health .
“ There is a high expectation that [ metabolomics ] will play a leading role in deciphering the interactions between diet and health , @ @ @ @ @ @ @ researcher at the University of Barcelona .
Before scientists can begin to link metabolites with health and disease , they must detail the relevant biomarkers for consumption of diverse foods .
In 2019 , Wishart and collaborators from Europe and New Zealand wrapped up a project that aimed to identify biomarkers for various foods and drinks , from Coca-Cola to chicken breast to Gruyère cheese .
Potential biomarkers include compounds directly derived from those foods or fluctuations in the concentrations of human metabolites or metabolites produced by the gut microbiome .
Called the @ @ @ @ @ @ @ the study turned up several promising candidates .
For example , the team investigating blood biomarkers for dairy proposed the sugar alcohol galactitol as an indicator for consumption of cow ’ s milk , and the aromatic compound 3-phenyllactic acid as a signal for cheese ingestion .
The FoodBAll collaborators also developed protocols for validating these novel biomarkers and created several online databases to fuel food metabolomics research .
( See table below . )
Even beyond the FoodBAll group , once researchers started looking , they found metabolites that reveal striking details @ @ @ @ @ @ @ biochemist Augustin Scalbert , of the International Agency for Research on Cancer , is interested in coffee , which comes in various types .
It ’ s also been linked to a range of health effects , so scientists want to know the best biomarkers for what kind , and how much , subjects consume .
Scalbert and colleagues compared blood metabolites from 451 individuals from four countries : France , where people often drink espresso ; Germany , where drip-filtered coffee is the norm ; Greece , where boiled coffee is preferred @ @ @ @ @ @ @ shot brewed by a percolator called a moka pot is popular .
In France and Germany , the alkaloid trigonelline was the best marker for coffee consumption .
But in Greece the best way to estimate someone ’ s coffee intake was quinic acid , Scalbert says , and in Italy , it was the amino acid derivative cyclo ( isoleucyl-prolyl ) .
The results suggest the ideal biomarkers might depend on the population under study .
Diet has long been linked to cancer risk .
But most studies have simply asked people @ @ @ @ @ @ @ later cancer diagnoses .
Like many nutrition researchers , epidemiologists at the American Cancer Society are now seeking specific markers for individual foods to obtain more-reliable data on diet-cancer links .
A couple of years ago , Marji McCullough and Ying Wang analyzed 1,186 serum metabolites from 91 food groups and individual items , based on a study of 1,369 women who had filled out food-frequency questionnaires as part of the Cancer Prevention Study II .
Correlations abounded : the scientists were able to connect 42 of those foods and food groups to @ @ @ @ @ @ @ , not-yet-named biomarkers for coffee and for dark fish , a category that includes sardines and salmon .
McCullough and her colleagues hope to validate and apply this profiling method to understand cancer risk in future studies .
“ The field is still young , ” she says .
Scalbert agrees .
“ We are learning , little by little , to exploit this information and make the best use of it to understand the link between food intake and different foods .
.
.
and different diets and the risk of cancer.
@ @ @ @ @ @ @ it is associated with a lower risk for liver cancer and its precursor , chronic liver disease .
Liver cancer affects about 33,000 Americans each year , according to the CDC , but a regular coffee habit slashes cancer risk by up to 50 percent .
Armed with their knowledge of coffee biomarkers , Scalbert and collaborators investigated banked blood samples collected from male smokers during a trial of nutritional supplements for the prevention of lung cancer in Finland in the 1980s .
In this dataset , coffee-drinking was associated with higher blood @ @ @ @ @ @ @ , glycerophospholipids that make up cell membranes , and trigonelline from the coffee beans themselves—and lower concentrations of tyrosine and bile acids .
Then , the researchers compared the data from trial participants who ’ d later been diagnosed with liver cancer or who died of liver disease before the end of 2012 with the data from volunteers in the same trial who had healthy livers .
Those healthy controls tended to have higher levels of the coffee compounds and associated molecules , while tyrosine and bile acids were higher in those who @ @ @ @ @ @ @ cancer .
“ This is a very nicely done and well-designed study , ” says Wishart , who was not involved in that particular piece of research but has collaborated with Scalbert on other projects .
He says the results fit with other studies suggesting that consuming coffee can diminish inflammation in the gut while promoting the growth of a beneficial microbiome—factors that then limit the damage caused by compounds such as bile acids and tyrosine .
What metabolites can tell us about overall diets Taking a more generalized view of eating habits @ @ @ @ @ @ @ quantify the overall healthfulness of a diet .
In the lock-in study , held at the UK ’ s National Institute for Health Research/Wellcome Trust Imperial Clinical Research Facility in London , he and his team fed their subjects four different meal plans : Diet 1 included foods considered healthy by the World Health Organization , including whole-wheat cereal , steamed salmon , and grapes .
Diet 4 represented the opposite end of the spectrum , with sugar-coated cereal , fried pork sausages , and milk chocolate .
Diets 2 and 3 fell @ @ @ @ @ @ @ a few days , the researchers could detect the effects of these menus in the subjects ’ metabolomic profiles .
For people eating the nourishing Diet 1 meals , 19 metabolites appeared at higher concentrations than they did in the urine of people consuming junk food–heavy Diet 4 .
One of those metabolites , for example , was hippurate , an indicator of fruit and vegetable consumption .
Conversely , nine metabolites were higher in people feasting on unhealthy Diet 4 than those on Diet 1 .
Carnitine , a biomarker for red @ @ @ @ @ @ @ these individual signals into a broader assessment , data scientist Joram Posma applied machine learning .
He used the biomarker levels from participants on Diet 1 or Diet 4 to train a computer algorithm to predict a person ’ s diet quality by profiling their urine .
Then , the team tested its model on the data from the intermediate diets .
Sure enough , the model correctly identified Diet 2 eaters as having relatively healthy metabolomes , and Diet 3 diners as skewing closer to the unhealthy patterns .
The team also @ @ @ @ @ @ @ Denmark and the UK .
Those with healthier reported diets had metabolomes more similar to those of locked-in subjects who ate Diet 1 .
“ This paper is interesting as it combines an intervention study with observational studies in two different cohorts , ” says Scalbert , who was not involved in the research .
“ This has often been done for specific foods , but more rarely for whole diets.
” Based on a metabolite profile , the team can now calculate a single Dietary Metabotype Score ( DMS ) to represent @ @ @ @ @ @ @ habits are.2 “ We can say where you are on the spectrum , ” says Frost .
Crucially , the scores are objective , with no interference from faulty recollections by eaters , adds Isabel Garcia-Perez , a chemist on the project who is now putting the algorithm into practice .
In a trial of clients seeing dieticians collaborating on the project , Garcia-Perez will use dietary scores to give providers an idea of a person ’ s eating habits before they meet , and to determine how closely clients follow , or @ @ @ @ @ @ @ eating plans .
She predicts that clients will be more motivated to keep up with the recommended diets if their metabolome provides frequent , reliable feedback on their adherence to the instructions .
McCullough and colleagues are seeking easy markers for broad dietary patterns in blood .
They specifically looked for metabolites that would likely indicate scores on four different diet measures : the alternate Mediterranean diet score , the alternate Healthy Eating Index , the Dietary Approaches to Stop Hypertension , and the Healthy Eating Index .
Top predictors for high scores @ @ @ @ @ @ @ diet , included markers for fish consumption such as the omega-3 fatty acid DHA , and the vitamin carotene from fruits and vegetables .
Ultimately , says McCullough , this kind of research may lead to affordable blood tests that indicate a person ’ s true dietary patterns—an objective measure that clinicians could use to assess disease risk and advise patients .
“ That ’ s far in the future , ” she says , “ but there ’ s a lot of potential.
” Amber Dance is a freelance science journalist living @ @ @ @ @ @ @ her work or reach out at AmberLDance.com .

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Between 2013 and 2014, 19 people were voluntarily locked in a clinic for days at a time—not once, but on four separate occasions. They were fed a different, strict diet on each of their three-day-long visits, and were forbidden to exercise. Computer access and visitation were allowed, so long as guests didn’t smuggle in snacks. Subjects turned over all their urine, from morning, afternoon, and night, to researchers.
These participants temporarily sacrificed their freedom to help dietician Gary Frost and colleagues at Imperial College London understand how eating habits influence the relative concentrations of metabolites excreted in urine, and thus how urine could serve as an indicator of a person’s diet, which in the team’s experiment ranged from healthy to gluttonous. Frost’s team anticipated that such metabolomics analyses would provide more-reliable data for nutritionists than the traditional tactic of asking free-roaming subjects what they’ve been noshing—an approach that is notorious for its huge error rates.
“Most people have a really bad memory of what they’re eating. . . . People will deny eating a dessert or forget that they ate a chocolate,” says David Wishart, a biochemist who works on metabolomics and nutrition at the University of Alberta but was not involved in Frost’s study. On the other hand, he adds, “blood and urine don’t lie.”
Blood and urine don’t lie. —David Wishart, University of Alberta
Indeed, Frost’s team was able to use the volunteers’ data to turn profiles of metabolites in urine into a single score, which they can now use to make inferences about the diets of people whose meals they didn’t control. Other researchers seeking objectivity in nutrition research are identifying metabolites that reveal if a person has consumed a specific food.
The approach is not yet perfected or widespread, and researchers are still working to define the metabolites linked to certain dietary qualities or foods. But with careful analyses, scientists are beginning to uncover nuanced information about people’s diets, such as how much milk and cheese they consume, or what kind of brew coffee drinkers drink. As the techniques improve and data on diet-metabolite correlations amass, researchers expect to standardize dietary epidemiology, which seeks to elucidate links between specific eating habits and disease risk. Some even see an opportunity to develop personalized nutrition recommendations to help people boost or maintain physical and mental health. Wishart, for example, is the chief informatics officer at a Vancouver-based company called Molecular You that uses metabolomics and other information to advise customers on eating habits to improve their health.
“There is a high expectation that [metabolomics] will play a leading role in deciphering the interactions between diet and health,” says Cristina Andrés-Lacueva, a nutrition researcher at the University of Barcelona.
Linking metabolites with specific foods
Before scientists can begin to link metabolites with health and disease, they must detail the relevant biomarkers for consumption of diverse foods. In 2019, Wishart and collaborators from Europe and New Zealand wrapped up a project that aimed to identify biomarkers for various foods and drinks, from Coca-Cola to chicken breast to Gruyère cheese. Potential biomarkers include compounds directly derived from those foods or fluctuations in the concentrations of human metabolites or metabolites produced by the gut microbiome. Called the Food Biomarker Alliance (FoodBAll), the study turned up several promising candidates.
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For example, the team investigating blood biomarkers for dairy proposed the sugar alcohol galactitol as an indicator for consumption of cow’s milk, and the aromatic compound 3-phenyllactic acid as a signal for cheese ingestion. The FoodBAll collaborators also developed protocols for validating these novel biomarkers and created several online databases to fuel food metabolomics research. (See table below.)
Even beyond the FoodBAll group, once researchers started looking, they found metabolites that reveal striking details about dietary habits. For example, biochemist Augustin Scalbert, of the International Agency for Research on Cancer, is interested in coffee, which comes in various types. It’s also been linked to a range of health effects, so scientists want to know the best biomarkers for what kind, and how much, subjects consume. Scalbert and colleagues compared blood metabolites from 451 individuals from four countries: France, where people often drink espresso; Germany, where drip-filtered coffee is the norm; Greece, where boiled coffee is preferred; and Italy, where an espresso-like shot brewed by a percolator called a moka pot is popular. In France and Germany, the alkaloid trigonelline was the best marker for coffee consumption. But in Greece the best way to estimate someone’s coffee intake was quinic acid, Scalbert says, and in Italy, it was the amino acid derivative cyclo(isoleucyl-prolyl). The results suggest the ideal biomarkers might depend on the population under study.
From Dinner Plate to Dataset To achieve greater objectivity in nutrition research, which has historically relied on self-reports of what subjects eat, scientists are turning to biomarkers in bodily fluids that reveal details about a person’s diet. Much of the work to this point has involved screens to identify novel markers for specific food items (or even for how those foods are prepared). In some cases, researchers have begun to use markers identified in these screens to correlate diet with health risks. KALAKAR In some studies that aim to identify metabolites associated with certain foods or diets, scientists tightly control people’s intakes before analyzing their metabolites. More often, they ask subjects what they’ve been eating. People’s bodies will contain molecules from the foods they eat, as well as metabolites made from or in response to those foods, and even metabolites from their microbiota. KALAKAR Most studies sample blood or urine, but stool, hair, or fingernails might also yield dietary clues. Mass spectrometry allows for highly sensitive analyses of these metabolites in any sample type, even picking up those found at low concentrations. Nuclear magnetic resonance (NMR) provides more reproducible results, but may miss rare molecules.
IMAGE COURTESY OF ISABEL GARCIA-PEREZ, JORAM POSMA, AND GARY FROST; DATA FROM
KALAKAR DATA DISPLAY ADAPTED FROM AM J CLIN NUTR , 102:905–13, 2015IMAGE COURTESY OF ISABEL GARCIA-PEREZ, JORAM POSMA, AND GARY FROST; DATA FROM NATURE FOOD , 1:355–64, 2020KALAKAR Results can reveal metabolites that are positively (red; example shown) or negatively (blue) associated with specific foods or correlate with the overall healthfulness of a diet.
PDF See full infographic: WEB
Researchers link metabolites with risk of specific diseases
Diet has long been linked to cancer risk. But most studies have simply asked people what they eat, and then tracked later cancer diagnoses.
Like many nutrition researchers, epidemiologists at the American Cancer Society are now seeking specific markers for individual foods to obtain more-reliable data on diet-cancer links. A couple of years ago, Marji McCullough and Ying Wang analyzed 1,186 serum metabolites from 91 food groups and individual items, based on a study of 1,369 women who had filled out food-frequency questionnaires as part of the Cancer Prevention Study II. Correlations abounded: the scientists were able to connect 42 of those foods and food groups to 199 different metabolites, including some novel, not-yet-named biomarkers for coffee and for dark fish, a category that includes sardines and salmon. McCullough and her colleagues hope to validate and apply this profiling method to understand cancer risk in future studies. “The field is still young,” she says.
Scalbert agrees. “We are learning, little by little, to exploit this information and make the best use of it to understand the link between food intake and different foods . . . and different diets and the risk of cancer.”
He was interested in coffee because it is associated with a lower risk for liver cancer and its precursor, chronic liver disease. Liver cancer affects about 33,000 Americans each year, according to the CDC, but a regular coffee habit slashes cancer risk by up to 50 percent. Armed with their knowledge of coffee biomarkers, Scalbert and collaborators investigated banked blood samples collected from male smokers during a trial of nutritional supplements for the prevention of lung cancer in Finland in the 1980s. In this dataset, coffee-drinking was associated with higher blood concentrations of several compounds—including the neurotransmitter serotonin, glycerophospholipids that make up cell membranes, and trigonelline from the coffee beans themselves—and lower concentrations of tyrosine and bile acids.
Then, the researchers compared the data from trial participants who’d later been diagnosed with liver cancer or who died of liver disease before the end of 2012 with the data from volunteers in the same trial who had healthy livers. Those healthy controls tended to have higher levels of the coffee compounds and associated molecules, while tyrosine and bile acids were higher in those who went on to develop liver disease or cancer.
“This is a very nicely done and well-designed study,” says Wishart, who was not involved in that particular piece of research but has collaborated with Scalbert on other projects. He says the results fit with other studies suggesting that consuming coffee can diminish inflammation in the gut while promoting the growth of a beneficial microbiome—factors that then limit the damage caused by compounds such as bile acids and tyrosine.
WHAT’S IN YOUR FOOD? Researchers involved in the FoodBAll project built several databases to facilitate research on food biomarkers. Database Description Details FooDB FooDB lists information on food components including biochemical makeup, health effects, and color, taste and smell. 70,926 compounds in 797 different foods Phenol-Explorer Polyphenols are plant compounds with documented health benefits. Phenol-Explorer lists chemical details, which foods contain the compounds, and whether they appear in blood or urine upon consumption. 500 polyphenols found in more than 400 foods PhytoHub PhytoHub lists polyphenols and other plant compounds, along with their metabolites produced by humans or other animals. 1,200 compounds in more than 350 foods Food Compound Exchange FoodComEx is a virtual library of food-derived compounds that different labs possess, so scientists can easily share them for study. 1,203 compounds
What metabolites can tell us about overall diets
Taking a more generalized view of eating habits, Frost and others are attempting to quantify the overall healthfulness of a diet. In the lock-in study, held at the UK’s National Institute for Health Research/Wellcome Trust Imperial Clinical Research Facility in London, he and his team fed their subjects four different meal plans: Diet 1 included foods considered healthy by the World Health Organization, including whole-wheat cereal, steamed salmon, and grapes. Diet 4 represented the opposite end of the spectrum, with sugar-coated cereal, fried pork sausages, and milk chocolate. Diets 2 and 3 fell in between those extremes.
Within just a few days, the researchers could detect the effects of these menus in the subjects’ metabolomic profiles. For people eating the nourishing Diet 1 meals, 19 metabolites appeared at higher concentrations than they did in the urine of people consuming junk food–heavy Diet 4. One of those metabolites, for example, was hippurate, an indicator of fruit and vegetable consumption. Conversely, nine metabolites were higher in people feasting on unhealthy Diet 4 than those on Diet 1. Carnitine, a biomarker for red meat, was one.
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To incorporate these individual signals into a broader assessment, data scientist Joram Posma applied machine learning. He used the biomarker levels from participants on Diet 1 or Diet 4 to train a computer algorithm to predict a person’s diet quality by profiling their urine. Then, the team tested its model on the data from the intermediate diets. Sure enough, the model correctly identified Diet 2 eaters as having relatively healthy metabolomes, and Diet 3 diners as skewing closer to the unhealthy patterns. The team also validated the model in other cohorts from Denmark and the UK. Those with healthier reported diets had metabolomes more similar to those of locked-in subjects who ate Diet 1.
“This paper is interesting as it combines an intervention study with observational studies in two different cohorts,” says Scalbert, who was not involved in the research. “This has often been done for specific foods, but more rarely for whole diets.”
Based on a metabolite profile, the team can now calculate a single Dietary Metabotype Score (DMS) to represent how healthy a person’s eating habits are.2 “We can say where you are on the spectrum,” says Frost.
Crucially, the scores are objective, with no interference from faulty recollections by eaters, adds Isabel Garcia-Perez, a chemist on the project who is now putting the algorithm into practice. In a trial of clients seeing dieticians collaborating on the project, Garcia-Perez will use dietary scores to give providers an idea of a person’s eating habits before they meet, and to determine how closely clients follow, or don’t follow, their prescribed eating plans. She predicts that clients will be more motivated to keep up with the recommended diets if their metabolome provides frequent, reliable feedback on their adherence to the instructions.
McCullough and colleagues are seeking easy markers for broad dietary patterns in blood. They specifically looked for metabolites that would likely indicate scores on four different diet measures: the alternate Mediterranean diet score, the alternate Healthy Eating Index, the Dietary Approaches to Stop Hypertension, and the Healthy Eating Index. Top predictors for high scores on these indices, reflecting a healthy diet, included markers for fish consumption such as the omega-3 fatty acid DHA, and the vitamin carotene from fruits and vegetables.
Ultimately, says McCullough, this kind of research may lead to affordable blood tests that indicate a person’s true dietary patterns—an objective measure that clinicians could use to assess disease risk and advise patients. “That’s far in the future,” she says, “but there’s a lot of potential.”
Personalized Nutrition While nutritionists agree on the basic ingredients of a healthy meal plan—lots of fruits and veggies, for example—the general guidelines don’t speak to differences between individual diners. “People respond to foods differently,” points out biochemist David Wishart of the University of Alberta. “Particularly with vitamins, there’s a fair bit of variability.” Vitamin processing may vary with age, genetic makeup, and physiology—for example, if someone is obese, fat-soluble vitamins might be stored in fat tissue instead of circulated through the body, he says. Thus, a glass of vitamin C–rich orange juice might in fact provide different vitamin C effects for different drinkers. That’s why he and others are developing personalized nutrition plans that recommend specific foods, supplements, or even exercises to improve health for individual clients. Wishart is the chief informatics officer for Molecular You, a company in Canada aiming to boost people’s health with detailed prescriptions based on metabolomics and other information. But at this point, some experts caution, it’s unclear how personalizing diets can improve the health of individuals, aside from populations with specific nutritional needs or allergies. In 2016, researchers from the Weizmann Institute of Science in Israel launched DayTwo, a company focused on blood-sugar control for people with type 2 diabetes and prediabetes. In diabetics, blood glucose spikes after eating can boost their risk for cardiovascular disease. DayTwo’s approach is based on a study published by its scientific cofounders in 2015. The scientists had monitored glucose levels continually for a week in 800 people as they collectively consumed nearly 47,000 meals (Cell, 163:1079–94, 2015). Using machine learning to incorporate glucose patterns, dietary habits, and other factors, the team developed an algorithm to predict glucose levels after consuming specific meals. The team then offered 12 new subjects the opportunity to receive dietary recommendations informed by its computer model. Participants worked with dieticians to devise meals that matched their preferences, then underwent glucose-level monitoring for a week while eating those meals to provide input data for the algorithm. The team then used the algorithm to predict “good” diets that avoided spikes, or “bad” diets that created them, for each individual. The subjects followed each of those diets for a week. Sure enough, blood-sugar spikes were higher in 10 people when they were on the “bad” diet. The algorithm performed as well as human experts in identifying whether meals would be “good” or “bad” for an individual, but outpaced the experts in that it could do the same for new meals, without any data on that person’s previous glucose responses to those foods. Molecular You launched its own metabolomics-based nutrition services to doctors in 2018, and to consumers last year. Company scientists delineated “safe” blood or urine concentrations for a slew of metabolites, based on the scientific literature and other sources. (The US Food and Drug Administration offers guidelines on safe levels of various compounds in foods, but not in bodily fluids.) Molecular You nutritionists combine company algorithms with their own experience to help customers reach those ideal ranges. A common, though not universal, recommendation is to eat less red meat, says company CEO Robert Fraser. Other tips are more individualized. For example, if people don’t have enough vitamin B, the company might recommend supplements. “There’s a lot of variety in what people need,” says Fraser. “There’s usually something very personal for each person.” In an as-yet unpublished study, the company analyzed about 150 customers who followed their Molecular You plan for 100 days. Those who stuck to the recommendation nudged all of their metabolite values into that “safe range,” Fraser says. Not everyone is ready to buy in. “I’m not a strong believer of personalized nutrition,” says Augustin Scalbert, a biochemist at the international Agency for Research on Cancer in France. Diet is just so complex, he explains, it will be difficult to prove any interventions are working.
Amber Dance is a freelance science journalist living in the Los Angeles area. Read her work or reach out at AmberLDance.com.


thescientist--2020-12-01--Citations Are the Currency of Science

Citations Are the Currency of Science

Scientific papers are the recordkeepers of progress in research .
Each year researchers publish millions of papers in more than 30,000 journals .
The scientific community measures the quality of those papers in a number of ways , including the perceived quality of the journal ( as reflected by the title ’ s impact factor ) and the number of citations a specific paper accumulates .
The careers of scientists and the reputation of their institutions depend on the number and prestige of the papers they produce , but even more so on the citations attracted by these papers .
@ @ @ @ @ @ @ several episodes of scientific fraud , including completely made-up data , massaged or doctored figures , multiple publications of the same data , theft of complete articles , plagiarism of text , and self-plagiarism .
And some scientists have come up with another way to artificially boost the number of citations to their work .
Citation cartels , where journals , authors , and institutions conspire to inflate citation numbers , have existed for a long time .
In 2016 , researchers developed an algorithm to recognize suspicious citation patterns , including groups @ @ @ @ @ @ @ and groups of journals that cite each other frequently to increase the impact factors of their publications .
Recently , I came across yet another expression of this predatory behavior : so-called support service consultancies that provide language and other editorial support to individual authors and to journals sometimes advise contributors to add a number of citations to their articles and the articles of colleagues .
Some of these consultancies are also active in organizing conferences and can advise that citations be added to conference proceedings .
In this manner , a single @ @ @ @ @ @ @ the direction of his own articles or those of colleagues that may be in his circle .
The advent of electronic publishing and authors ’ need to find outlets for their papers resulted in thousands of new journals , frequently with the imprimatur of “ international ” and promises of open access and wide circulation .
The birth of predatory journals wasn ’ t far behind .
Recently a group of authors published a consensus definition of such publications : “ Predatory journals and publishers are entities that prioritize self-interest at the expense @ @ @ @ @ @ @ or misleading information , deviation from best editorial and publication practices , a lack of transparency , and/or the use of aggressive and indiscriminate solicitation practices.
” These journals can act as milk cows where every single article in an issue may cite a specific paper or a series of papers .
Sometimes the citations are more or less on topic , but in other instances , there is absolutely no relationship between the content of the article and the citations .
The peculiar part is that the journal that the editor is @ @ @ @ @ @ @ all—it is just providing citations to other journals .
It ’ s easy enough to spot if someone at the journal would pay attention .
Such practices can lead an article to accrue more than 150 citations in the same year that it was published .
How insidious is this type of citation manipulation ?
In one example , an individual—acting as author , editor , and consultant—was able to use at least 15 journals as citation providers to articles published by five scientists at three universities .
The problem is rampant in @ @ @ @ @ @ @ of the new “ international ” journals .
In fact , a listing in Scopus seems to be a criterion to be targeted in this type of citation manipulation .
Why is this important ?
First , these individuals who are not only authors , but also editors and consultants , and their colleagues obtain hundreds of citations and outshine their colleagues who play by the rules .
Guess who ’ s more likely to get tenure or that plum promotion ?
Second , the numbers are staggering .
For one university , @ @ @ @ @ @ @ Scopus-listed papers its researchers published in 2019 , the citation numbers of at least 20 appear to have been boosted in this way .
Almost 60 percent of the citations to published studies from this university came from 15 manipulated journals , and this significantly padded the citation numbers of the 20 articles .
These suspect citations drove the citations per paper ( C/P ) average for this university up to 2.50 for the year , whereas without them , the C/P would have been 1.08 .
Because citations per paper and/or citations @ @ @ @ @ @ @ Symonds ranking and the Times Higher Education World University Rankings , this also artificially inflates the quantitative standing of the university .
What can be done about citation cartels ?
First , editors and editorial boards of legitimate journals should be paying attention and correcting their colleagues .
They carry a responsibility .
When every single article in a journal is citing a specific article or group of articles , something is likely amiss .
When the subjects of the cited and citing articles are unrelated , it is a dead giveaway .
@ @ @ @ @ @ @ this could be analyzed .
In fact , checking for appropriateness of citations is a major task for reviewers and editors .
Journals should also reconsider the practice of using outside support service consultants as editors of articles or special issues that result from conferences .
Scopus itself has all the data necessary to detect this malpractice .
Red flags include a large number of citations to an article within the first year .
And for authors who wish to steer clear of citation cartel activities : when an editor , a reviewer @ @ @ @ @ @ @ to add inappropriate references , do not oblige and do report the request to the journal .
Sibrandes Poppema is the Tan Sri Jeffrey Cheah Distinguished Professor at Sunway University in Malaysia and is president emeritus of the University of Groningen in the Netherlands .

ABOVE: © ISTOCK.COM, BOBBOZ
Scientific papers are the recordkeepers of progress in research. Each year researchers publish millions of papers in more than 30,000 journals. The scientific community measures the quality of those papers in a number of ways, including the perceived quality of the journal (as reflected by the title’s impact factor) and the number of citations a specific paper accumulates. The careers of scientists and the reputation of their institutions depend on the number and prestige of the papers they produce, but even more so on the citations attracted by these papers.
In recent years, there have been several episodes of scientific fraud, including completely made-up data, massaged or doctored figures, multiple publications of the same data, theft of complete articles, plagiarism of text, and self-plagiarism. And some scientists have come up with another way to artificially boost the number of citations to their work.
Citation cartels, where journals, authors, and institutions conspire to inflate citation numbers, have existed for a long time. In 2016, researchers developed an algorithm to recognize suspicious citation patterns, including groups of authors that disproportionately cite one another and groups of journals that cite each other frequently to increase the impact factors of their publications. Recently, I came across yet another expression of this predatory behavior: so-called support service
consultancies that provide language and other editorial support to individual authors and to journals sometimes advise contributors to add a number of citations to their articles and the articles of colleagues. Some of these consultancies are also active in organizing conferences and can advise that citations be added to conference proceedings. In this manner, a single editor can drive hundreds of citations in the direction of his own articles or those of colleagues that may be in his circle.
Citation cartels, where journals, authors, and institutions conspire to inflate citation numbers, have existed for a long time.
The advent of electronic publishing and authors’ need to find outlets for their papers resulted in thousands of new journals, frequently with the imprimatur of “international” and promises of open access and wide circulation. The birth of predatory journals wasn’t far behind. Recently a group of authors published a consensus definition of such publications: “Predatory journals and publishers are entities that prioritize self-interest at the expense of scholarship and are characterized by false or misleading information, deviation from best editorial and publication practices, a lack of transparency, and/or the use of aggressive and indiscriminate solicitation practices.”
These journals can act as milk cows where every single article in an issue may cite a specific paper or a series of papers. Sometimes the citations are more or less on topic, but in other instances, there is absolutely no relationship between the content of the article and the citations. The peculiar part is that the journal that the editor is supposedly working for is not profiting at all—it is just providing citations to other journals. It’s easy enough to spot if someone at the journal would pay attention. Such practices can lead an article to accrue more than 150 citations in the same year that it was published.
How insidious is this type of citation manipulation? In one example, an individual—acting as author, editor, and consultant—was able to use at least 15 journals as citation providers to articles published by five scientists at three universities. The problem is rampant in Scopus, which includes a high number of the new “international” journals. In fact, a listing in Scopus seems to be a criterion to be targeted in this type of citation manipulation.
Why is this important? First, these individuals who are not only authors, but also editors and consultants, and their colleagues obtain hundreds of citations and outshine their colleagues who play by the rules. Guess who’s more likely to get tenure or that plum promotion? Second, the numbers are staggering. For one university, I found that of the nearly 700 Scopus-listed papers its researchers published in 2019, the citation numbers of at least 20 appear to have been boosted in this way. Almost 60 percent of the citations to published studies from this university came from 15 manipulated journals, and this significantly padded the citation numbers of the 20 articles. These suspect citations drove the citations per paper (C/P) average for this university up to 2.50 for the year, whereas without them, the C/P would have been 1.08. Because citations per paper and/or citations per faculty are criteria in the Quacquarelli Symonds ranking and the Times Higher Education World University Rankings, this also artificially inflates the quantitative standing of the university.
What can be done about citation cartels? First, editors and editorial boards of legitimate journals should be paying attention and correcting their colleagues. They carry a responsibility. When every single article in a journal is citing a specific article or group of articles, something is likely amiss. When the subjects of the cited and citing articles are unrelated, it is a dead giveaway. Before publication of a journal issue, this could be analyzed. In fact, checking for appropriateness of citations is a major task for reviewers and editors. Journals should also reconsider the practice of using outside support service consultants as editors of articles or special issues that result from conferences.
Scopus itself has all the data necessary to detect this malpractice. Red flags include a large number of citations to an article within the first year. And for authors who wish to steer clear of citation cartel activities: when an editor, a reviewer, or a support service asks you to add inappropriate references, do not oblige and do report the request to the journal.
Sibrandes Poppema is the Tan Sri Jeffrey Cheah Distinguished Professor at Sunway University in Malaysia and is president emeritus of the University of Groningen in the Netherlands.


thescientist--2020-12-01--Science Is My Copilot

Science Is My Copilot

Sitting down to write this editorial , I thought I would look back at the one I wrote for our first issue of 2020 to get a sense , at the end of an extremely unpredictable and disconcerting year , of how I was feeling going into it .
“ In those halcyon days of boyhood , one date stuck in my mind as ‘ the future ’ —2020 , ” I wrote in The Scientist ’ s January/February 2020 issue .
“ That year , difficult to imagine but endlessly entertaining to dream about , was when everything would @ @ @ @ @ @ @ a reality .
Technology would solve humanity ’ s and the planet ’ s ailments .
And yes , cars would fly.
” I knew that my childish fantasies had failed to materialize well in advance of last January , but early in the year I had no idea how wrong I would be about 2020 .
This year has shown us all that , despite humanity ’ s decades of scientific , technological , and social progress , nature ( human and otherwise ) still harbors the power to bring us to @ @ @ @ @ @ @ the time required to go from futuristic dream to dystopian nightmare is the veritable blink of an eye .
I , like the rest of us , have been trying my best to cope with the harsh new realities of the worst infectious disease pandemic in a century .
One of the things that buoyed my spirit in the darkest hours was the sense that the life science community was rising to the challenge of COVID-19 , with several labs pivoting to study the disease and the virus that causes it ; drug @ @ @ @ @ @ @ of tests , treatments , and vaccines ; and researchers anticipating the need to study the societal and mental health effects of the pandemic .
Other times , despondency took over , as news of publication misconduct surrounding COVID-19 broke and it became apparent that , in some countries , policy and science regarding the appropriate path toward coronavirus mitigation were seriously out of step .
Still , as I reflect on 2020 , I see the heartbeat of research pulsing through the turmoil , even when science was sidelined , ignored , @ @ @ @ @ @ @ the face of numerous challenges can be seen in the pages of this issue , where we highlight the winners of our annual Top 10 Innovations competition ( see page 38 ) .
Several of the winning submissions—including a rapid and portable SARS-CoV-2 test and antibody kits to help characterize the plasma of patients who have recovered from COVID-19 , to name but a couple—address the pandemic head-on .
Other winning products represent advanced development of tried-and-true laboratory technologies , such as microfluidics and single-cell analyses , that could potentially help battle the @ @ @ @ @ @ @ , as I write this piece , news broke about the Pfizer/BioNTech and Moderna vaccines being reportedly more than 90 percent effective in Phase 3 trials .
These results are preliminary , but the scientific community and the world are responding with all the hope and positivity that one might expect .
It is my sincere hope that 2021 will be a better year than 2020 .
If this is to happen , research must continue to forge ahead , unimpeded by politicization and supported by the public , governments , and private @ @ @ @ @ @ @ been clearer that evidence , logic , and science are the keys to delivering us from the suffering of the past several months and the months to come .
We at The Scientist look forward to a new year and to following and reporting on the innovation and discovery that rise from the ashes of 2020 .
There will be much to keep tabs on , from continued vaccine development and testing to the long-term biological impacts of COVID-19 .
As case numbers rise around the world , and especially in the US @ @ @ @ @ @ @ challenges and heartbreak ahead .
But we will keep a close eye on the possible paths out of this pandemic , with science as our touchstone and navigator .

ABOVE: ISTOCK.COM, JANIECBROS
Sitting down to write this editorial, I thought I would look back at the one I wrote for our first issue of 2020 to get a sense, at the end of an extremely unpredictable and disconcerting year, of how I was feeling going into it. “In those halcyon days of boyhood, one date stuck in my mind as ‘the future’—2020,” I wrote in The Scientist’s January/February 2020 issue. “That year, difficult to imagine but endlessly entertaining to dream about, was when everything would be different. World peace would be a reality. Technology would solve humanity’s and the planet’s ailments. And yes, cars would fly.”
I knew that my childish fantasies had failed to materialize well in advance of last January, but early in the year I had no idea how wrong I would be about 2020. This year has shown us all that, despite humanity’s decades of scientific, technological, and social progress, nature (human and otherwise) still harbors the power to bring us to our knees. We also learned that the time required to go from futuristic dream to dystopian nightmare is the veritable blink of an eye.
ANDRZEJ KRAUZE
I, like the rest of us, have been trying my best to cope with the harsh new realities of the worst infectious disease pandemic in a century. One of the things that buoyed my spirit in the darkest hours was the sense that the life science community was rising to the challenge of COVID-19, with several labs pivoting to study the disease and the virus that causes it; drug companies and independent scientists speeding the development of tests, treatments, and vaccines; and researchers anticipating the need to study the societal and mental health effects of the pandemic. Other times, despondency took over, as news of publication misconduct surrounding COVID-19 broke and it became apparent that, in some countries, policy and science regarding the appropriate path toward coronavirus mitigation were seriously out of step.
Still, as I reflect on 2020, I see the heartbeat of research pulsing through the turmoil, even when science was sidelined, ignored, or contravened. Evidence of discovery in the face of numerous challenges can be seen in the pages of this issue, where we highlight the winners of our annual Top 10 Innovations competition (see page 38). Several of the winning submissions—including a rapid and portable SARS-CoV-2 test and antibody kits to help characterize the plasma of patients who have recovered from COVID-19, to name but a couple—address the pandemic head-on. Other winning products represent advanced development of tried-and-true laboratory technologies, such as microfluidics and single-cell analyses, that could potentially help battle the scourge of COVID-19.
And in mid-November, as I write this piece, news broke about the Pfizer/BioNTech and Moderna vaccines being reportedly more than 90 percent effective in Phase 3 trials. These results are preliminary, but the scientific community and the world are responding with all the hope and positivity that one might expect.
It is my sincere hope that 2021 will be a better year than 2020. If this is to happen, research must continue to forge ahead, unimpeded by politicization and supported by the public, governments, and private parties alike. Never before has it been clearer that evidence, logic, and science are the keys to delivering us from the suffering of the past several months and the months to come.
We at The Scientist look forward to a new year and to following and reporting on the innovation and discovery that rise from the ashes of 2020. There will be much to keep tabs on, from continued vaccine development and testing to the long-term biological impacts of COVID-19. As case numbers rise around the world, and especially in the US, we know that there are more challenges and heartbreak ahead. But we will keep a close eye on the possible paths out of this pandemic, with science as our touchstone and navigator.
Bob Grant
Editor-in-Chief


Contributors

As a medical student at the University of Groningen in the Netherlands , Sibrandes Poppema worked in a pathology lab , and he enjoyed the research so much that he decided to also pursue a doctorate in pathology .
Poppema says he immediately set his sights on studying Hodgkin ’ s disease , a type of lymphoma .
“ It ’ s a cancer , ” he says , “ but it ’ s a cancer where less than one percent of it is tumor cells—ninety-nine percent are reactive cells , ” immune cells that are reacting to something in @ @ @ @ @ @ @ degree in 1974 and his pathology doctorate in 1979 , he completed two postdocs , one at the Christian-Albrecht University of Kiel in Germany and one at Harvard Medical School in Boston , before returning to the University of Groningen as an immunopathology professor .
In 1987 , he moved to Canada to join the leadership of the Cross Cancer Institute at the University of Alberta , but after eight years again returned to the University of Groningen , where he served as the pathology department chair , then dean of medical faculty @ @ @ @ @ @ @ university .
A couple years ago , he moved to Malaysia to become a professor at Sunway University , where he is lobbying the Malaysian government to open a new medical school .
Over the course of his career , Poppema recalls looking at the CVs of some prospective graduate students and feeling impressed by a high number of citations on their publications .
But , after further investigation , Poppema was dismayed to learn that , in some cases , many of those citations were all a bunch of “ gobbledygook ” @ @ @ @ @ @ @ bulk of the citations .
In this issue , he writes about this practice , which he calls “ citation padding.
” The practice , he says , is “ simply not fair.
” When Antonio Zadra was a teenager , he had a lucid dream that changed the course of his career .
After that dream , he began keeping a dream diary and devoured every book in the library on sleep and dreams .
He graduated from McGill University with a bachelor ’ s degree in psychology and stayed there to @ @ @ @ @ @ @ He eventually earned a master ’ s in experimental psychology and a doctorate in clinical psychology .
Zadra ’ s own dreams continue to influence his research interests today at the Université de Montréal , where he is a psychology professor .
He says he is fascinated by recurring characters in his dreams , the neurobiology of parasomnias such as sleepwalking , and the origins and content of nightmares .
Robert Stickgold didn ’ t research dreams until much later in his career .
He graduated from Harvard University with a bachelor ’ @ @ @ @ @ @ @ received a doctorate in biochemistry from the University of Wisconsin–Madison in 1972 .
Stickgold first became interested in dreaming when he read an article by psychiatrist Allan Hobson that argued that the content of dreams was essentially random—an assertion that Stickgold rejected .
Despite their differences in opinion , he went on to work in Hobson ’ s lab before becoming a psychiatry professor at Beth Israel Deaconess Medical Center and Harvard Medical School , where he studies the function of sleep and dreams on memory consolidation and how defects in this process @ @ @ @ @ @ @ sleep conference a few years ago , Zadra asked Stickgold if he wanted to coauthor a journal article on pervasive myths about dreams , but their list grew so long that the two decided to write an entire book—When Brains Dream , which publishes in January 2021 .
In this issue , read an essay from the pair about the possible functions of dreaming .
Max Kozlov ’ s interest in science started early .
His family had immigrated from Ukraine to the Boston area a few years before Kozlov was born , @ @ @ @ @ @ @ couldn ’ t speak English .
His grandparents would often take him to the city ’ s Museum of Science , “ and they had a lot of interactive exhibit components that didn ’ t require you to know English , ” he says .
“ I think that made me curious about the world around me.
” He went on to work at the museum while in high school , giving him an early taste of science communication .
Around the same time , he also began volunteering to be a subject @ @ @ @ @ @ @ ’ s participated in around 40 so far .
They pay well , he explains , and “ I ’ m so curious what researchers are working on and what it ’ s like to be in a research study.
” Kozlov studied cognitive neuroscience at Brown University , and , after graduating in May of this year , went on to do a AAAS Mass Media Fellowship at the St. Louis Post-Dispatch .
“ I found myself , and I still find myself thinking , ‘ Man , I have the coolest @ @ @ @ @ @ @ call up people and listen to them talk about .
.
.
what motivates them , and hear about some of the coolest research that ’ s going on , and every single day I learn something completely new , ’ ” he says .
Currently an intern with The Scientist , Kozlov has already written multiple stories for the website , and his first pieces for the print magazine appear in this issue : a profile of Gloria Echeverria and a story about giant , ancient sperm .

NOR HIDAYAH HASSAN, SUNWAY CORPORATION
As a medical student at the University of Groningen in the Netherlands, Sibrandes Poppema worked in a pathology lab, and he enjoyed the research so much that he decided to also pursue a doctorate in pathology. Poppema says he immediately set his sights on studying Hodgkin’s disease, a type of lymphoma. “It’s a cancer,” he says, “but it’s a cancer where less than one percent of it is tumor cells—ninety-nine percent are reactive cells,” immune cells that are reacting to something in their environment. After receiving his medical degree in 1974 and his pathology doctorate in 1979, he completed two postdocs, one at the Christian-Albrecht University of Kiel in Germany and one at Harvard Medical School in Boston, before returning to the University of Groningen as an immunopathology professor. In 1987, he moved to Canada to join the leadership of the Cross Cancer Institute at the University of Alberta, but after eight years again returned to the University of Groningen, where he served as the pathology department chair, then dean of medical faculty, and finally, president of the university. A couple years ago, he moved to Malaysia to become a professor at Sunway University, where he is lobbying the Malaysian government to open a new medical school.
Over the course of his career, Poppema recalls looking at the CVs of some prospective graduate students and feeling impressed by a high number of citations on their publications. But, after further investigation, Poppema was dismayed to learn that, in some cases, many of those citations were all a bunch of “gobbledygook”—a few obscure journals made up the bulk of the citations. In this issue, he writes about this practice, which he calls “citation padding.” The practice, he says, is “simply not fair.”
VINCENT ZADRA
When Antonio Zadra was a teenager, he had a lucid dream that changed the course of his career. After that dream, he began keeping a dream diary and devoured every book in the library on sleep and dreams. He graduated from McGill University with a bachelor’s degree in psychology and stayed there to pursue graduate studies focused on dreaming. He eventually earned a master’s in experimental psychology and a doctorate in clinical psychology. Zadra’s own dreams continue to influence his research interests today at the Université de Montréal, where he is a psychology professor. He says he is fascinated by recurring characters in his dreams, the neurobiology of parasomnias such as sleepwalking, and the origins and content of nightmares.
BRUCE WAHL, BIDMC
Robert Stickgold didn’t research dreams until much later in his career. He graduated from Harvard University with a bachelor’s degree in biochemistry in 1966 and received a doctorate in biochemistry from the University of Wisconsin–Madison in 1972. Stickgold first became interested in dreaming when he read an article by psychiatrist Allan Hobson that argued that the content of dreams was essentially random—an assertion that Stickgold rejected. Despite their differences in opinion, he went on to work in Hobson’s lab before becoming a psychiatry professor at Beth Israel Deaconess Medical Center and Harvard Medical School, where he studies the function of sleep and dreams on memory consolidation and how defects in this process contribute to psychiatric disorders.
At a sleep conference a few years ago, Zadra asked Stickgold if he wanted to coauthor a journal article on pervasive myths about dreams, but their list grew so long that the two decided to write an entire book—When Brains Dream, which publishes in January 2021. In this issue, read an essay from the pair about the possible functions of dreaming.
LAUREN SHIN
Max Kozlov’s interest in science started early. His family had immigrated from Ukraine to the Boston area a few years before Kozlov was born, and as a young child, he couldn’t speak English. His grandparents would often take him to the city’s Museum of Science, “and they had a lot of interactive exhibit components that didn’t require you to know English,” he says. “I think that made me curious about the world around me.” He went on to work at the museum while in high school, giving him an early taste of science communication. Around the same time, he also began volunteering to be a subject in research studies; he estimates he’s participated in around 40 so far. They pay well, he explains, and “I’m so curious what researchers are working on and what it’s like to be in a research study.”
Kozlov studied cognitive neuroscience at Brown University, and, after graduating in May of this year, went on to do a AAAS Mass Media Fellowship at the St. Louis Post-Dispatch. “I found myself, and I still find myself thinking, ‘Man, I have the coolest job, because I just get to call up people and listen to them talk about . . . what motivates them, and hear about some of the coolest research that’s going on, and every single day I learn something completely new,’” he says. Currently an intern with The Scientist, Kozlov has already written multiple stories for the website, and his first pieces for the print magazine appear in this issue: a profile of Gloria Echeverria and a story about giant, ancient sperm.


thescientist--2020-12-01--Infographic: Deciphering Diet from Blood and Urine Samples

To achieve greater objectivity in nutrition research , which has historically relied on self-reports of what subjects eat , scientists are turning to biomarkers in bodily fluids that reveal details about a person ’ s diet .
Much of the work to this point has involved screens to identify novel markers for specific food items ( or even for how those foods are prepared ) .
In some cases , researchers have begun to use markers identified in these screens to correlate diet with health risks .
In some studies that aim to identify metabolites associated with certain foods or @ @ @ @ @ @ @ s intakes before analyzing their metabolites .
More often , they ask subjects what they ’ ve been eating .
People ’ s bodies will contain molecules from the foods they eat , as well as metabolites made from or in response to those foods , and even metabolites from their microbiota .
Most studies sample blood or urine , but stool , hair , or fingernails might also yield dietary clues .
Mass spectrometry allows for highly sensitive analyses of these metabolites in any sample type , even picking up those found @ @ @ @ @ @ @ ( NMR ) provides more reproducible results , but may miss rare molecules .
Results can reveal metabolites that are positively ( red ; example shown ) or negatively ( blue ) associated with specific foods or correlate with the overall healthfulness of a diet .

ABOVE: KALAKAR
To achieve greater objectivity in nutrition research, which has historically relied on self-reports of what subjects eat, scientists are turning to biomarkers in bodily fluids that reveal details about a person’s diet. Much of the work to this point has involved screens to identify novel markers for specific food items (or even for how those foods are prepared). In some cases, researchers have begun to use markers identified in these screens to correlate diet with health risks.
KALAKAR
In some studies that aim to identify metabolites associated with certain foods or diets, scientists tightly control people’s intakes before analyzing their metabolites. More often, they ask subjects what they’ve been eating. People’s bodies will contain molecules from the foods they eat, as well as metabolites made from or in response to those foods, and even metabolites from their microbiota.
KALAKAR
Most studies sample blood or urine, but stool, hair, or fingernails might also yield dietary clues. Mass spectrometry allows for highly sensitive analyses of these metabolites in any sample type, even picking up those found at low concentrations. Nuclear magnetic resonance (NMR) provides more reproducible results, but may miss rare molecules.
IMAGE COURTESY OF ISABEL GARCIA-PEREZ, JORAM POSMA, AND GARY FROST; DATA FROM
KALAKAR DATA DISPLAY ADAPTED FROM AM J CLIN NUTR , 102:905–13, 2015IMAGE COURTESY OF ISABEL GARCIA-PEREZ, JORAM POSMA, AND GARY FROST; DATA FROM NATURE FOOD , 1:355–64, 2020KALAKAR
Results can reveal metabolites that are positively (red; example shown) or negatively (blue) associated with specific foods or correlate with the overall healthfulness of a diet.
Read the full story.


thescientist--2020-12-01--Unearthed: World’s Oldest Animal Sperm—And It’s Giant

ABOVE : STUCK IN AMBER : The record-setting sperm was found in a new ostracod species called Myanmarcypris hui .
HE WANG & XIANGDONG ZHAO , NANJING UNIVERSITY The paper H. Wang et al.
, “ Exceptional preservation of reproductive organs and giant sperm in Cretaceous ostracods , ” Proc R Soc B , 287:20201661 , 2020 .
Something giant lingers in a tiny piece of amber the size of a postage stamp .
It ’ s the world ’ s oldest sperm , and it ’ s relatively big—nearly five times longer than the creature from which it came @ @ @ @ @ @ @ years and belongs to an ancient ostracod , a relative of millimeter-long crustaceans still alive today .
It ’ s almost 50 million years older than the previously catalogued oldest sperm , according to Nanjing University paleontologists He Wang and Bo Wang , who studied it .
Timing was key to the perfect preservation of the sperm , which is rarely fossilized .
The researchers found a tangled clump of sperm and four tiny eggs in a female that was petrified in amber along with 38 other females , males , and juveniles @ @ @ @ @ @ @ that had not been identified before .
Because the sperm was still inside the female , she must have mated “ maybe a matter of minutes or hours before ” tree resin fell and trapped her , study coauthor David Horne , a paleontologist at Queen Mary University of London , tells The Scientist .
Not only was finding the sperm surprising , but so was how much sperm was in the female .
Modern ostracods produce the largest volume of spermatozoa in the animal kingdom .
As it turns out , ancient @ @ @ @ @ @ @ hundred million years ago .
Producing voluminous sperm , even though it takes a lot of energy , can physically block other sperm from penetrating the egg .
And it appears to have been an evolutionarily advantageous strategy of reproduction for longer than researchers thought , the scientists say .
“ There are a couple of categories of stories that gather a lot of attention in paleontology : one is exceptional preservation and the other is weird sex stuff , ” says Gene Hunt , a paleobiologist at the Smithsonian National Museum of @ @ @ @ @ @ @ the study .
“ This is a perfect intersection of those two kinds of stories .
”

ABOVE: STUCK IN AMBER: The record-setting sperm was found in a new ostracod species called Myanmarcypris hui.
HE WANG & XIANGDONG ZHAO, NANJING UNIVERSITY
EDITOR’S CHOICE IN PALEONTOLOGY
The paper
H. Wang et al., “Exceptional preservation of reproductive organs and giant sperm in Cretaceous ostracods,” Proc R Soc B, 287:20201661, 2020.
Something giant lingers in a tiny piece of amber the size of a postage stamp. It’s the world’s oldest sperm, and it’s relatively big—nearly five times longer than the creature from which it came.
The sperm dates back 100 million years and belongs to an ancient ostracod, a relative of millimeter-long crustaceans still alive today. It’s almost 50 million years older than the previously catalogued oldest sperm, according to Nanjing University paleontologists He Wang and Bo Wang, who studied it.
Timing was key to the perfect preservation of the sperm, which is rarely fossilized. The researchers found a tangled clump of sperm and four tiny eggs in a female that was petrified in amber along with 38 other females, males, and juveniles, belonging to a genus of ostracods that had not been identified before. Because the sperm was still inside the female, she must have mated “maybe a matter of minutes or hours before” tree resin fell and trapped her, study coauthor David Horne, a paleontologist at Queen Mary University of London, tells The Scientist.
Not only was finding the sperm surprising, but so was how much sperm was in the female. Modern ostracods produce the largest volume of spermatozoa in the animal kingdom. As it turns out, ancient ostracods also produced really large sperm a hundred million years ago. Producing voluminous sperm, even though it takes a lot of energy, can physically block other sperm from penetrating the egg. And it appears to have been an evolutionarily advantageous strategy of reproduction for longer than researchers thought, the scientists say.
“There are a couple of categories of stories that gather a lot of attention in paleontology: one is exceptional preservation and the other is weird sex stuff,” says Gene Hunt, a paleobiologist at the Smithsonian National Museum of Natural History who was not involved with the study. “This is a perfect intersection of those two kinds of stories.”


thescientist--2020-12-01--Opinion: The Biological Function of Dreams

At the start of the 21st century , scientists had little idea why we sleep , leading J. Allan Hobson at Harvard Medical School to quip that the only known function of sleep was to cure sleepiness .
But 20 years later , we know a lot more .
It turns out that for every two hours a person is awake and interacting with the world , the brain on average needs to go “ offline ” for an hour—disconnected from the outside world—to process and contextualize those experiences .
Sleep benefits memory in myriad ways .
For simple procedural @ @ @ @ @ @ @ between different coins in one ’ s pocket—a night of sleep or an afternoon nap following learning leads to a dramatic improvement in performance .
Sleep also stabilizes verbal memories , reducing their susceptibility to interference and decay , processes that all too easily lead to forgetting .
But the action of sleep can be more sophisticated than simply strengthening and stabilizing memories .
It can lead to the selective retention of emotional memories , or even of emotional components of a scene , while allowing other memories and parts of a scene @ @ @ @ @ @ @ ability to extract the gist from a list of words , or the rules governing a complex probabilistic game .
It can lead to insights ranging from finding the single word that logically connects three apparently unrelated words , to discovering an unexpected rule that allows for the more efficient solving of mathematical problems .
It can facilitate the integration of new information into existing networks of related information .
And it has been shown to help infants gain language skills .
Disruptions of normal sleep in neurologic and psychiatric disorders can lead @ @ @ @ @ @ @ As we describe in our upcoming book When Brains Dream , dreams appear to be part of this ongoing memory processing , and their occurrence and content can predict subsequent memory improvement .
While there is a vigorous debate over whether the actual conscious experiencing of dreams while they occur serves a function , we believe that it does , and that it is similar to that proposed for waking consciousness .
Antonio Damasio , in this 2000 book The Feeling of What Happens , argues that consciousness provides two critical functions to @ @ @ @ @ @ @ and to feel one ’ s emotional response to them .
Together , they give humans ( and presumably other conscious animals ) the ability to imagine possibilities , evaluate them , and thereby plan future actions .
Our NEXTUP model of dreaming ( Network Exploration to Understand Possibilities ) proposes that dreaming serves a similar function .
Specifically , we argue that dreaming allows the sleeping brain to enter an altered state of consciousness in which it can construct imagined narratives and respond emotionally to them .
While dreaming , the brain @ @ @ @ @ @ @ typically from the preceding day ) and older , often only weakly related memories , and monitors whether the narrative it constructs from these memories induces an emotional response in the brain .
If an emotional feeling is detected , the brain tags the association as potentially valuable , strengthening the link between the two memories and making the association available during subsequent wakefulness .
But dreaming is different from waking consciousness .
First , the dreaming brain can not access and incorporate complete episodic memories ( i.e.
, memories of actual events @ @ @ @ @ @ @ associative exploration of dreams is limited to semantic and nondeclarative memories ( i.e.
, memories related to general world knowledge and those acquired and used unconsciously , respectively ) .
In other words , while imagining and planning during wakefulness is normally based on recalled events , narrative construction during dreaming is based on semantic associations of these events , giving dreams their metaphorical quality and allowing for a more expansive investigation of associative links .
Second , the neurochemical modulation of the brain is altered during sleep , and especially during rapid @ @ @ @ @ @ @ when the release of norepinephrine and serotonin in the brain is shut off while levels of acetylcholine reach their peak in regions such as the hippocampus .
These shifts bias memory networks toward the activation of normally weak associations , perhaps explaining the bizarreness of many dreams , especially during REM sleep .
Third , REM sleep is accompanied by a general activation of the limbic system , presumably explaining the enhanced emotionality seen in REM dreams , while also biasing the brain toward creating emotional responses to imagined dream narratives .
Finally @ @ @ @ @ @ @ relies on imagining and planning , dreaming stops short of offering definitive solutions to our current concerns .
Instead , our dreams serve to explore the solution space , helping us to discover new possibilities .
It is up to other processes , both in wakefulness and sleep , to draw conclusions and delineate our plans .
Dreaming takes what has been and shows us what might be .
Robert Stickgold is a professor at Harvard Medical School and director of the Center for Sleep and Cognition .
Antonio Zadra is a professor @ @ @ @ @ @ @ researcher at the Center for Advanced Research in Sleep Medicine .
Read an excerpt of When Brains Dream .

ABOVE: © ISTOCK.COM, metamorworks
At the start of the 21st century, scientists had little idea why we sleep, leading J. Allan Hobson at Harvard Medical School to quip that the only known function of sleep was to cure sleepiness. But 20 years later, we know a lot more. It turns out that for every two hours a person is awake and interacting with the world, the brain on average needs to go “offline” for an hour—disconnected from the outside world—to process and contextualize those experiences.
Sleep benefits memory in myriad ways. For simple procedural skills—how to ride a bicycle or distinguish between different coins in one’s pocket—a night of sleep or an afternoon nap following learning leads to a dramatic improvement in performance. Sleep also stabilizes verbal memories, reducing their susceptibility to interference and decay, processes that all too easily lead to forgetting.
But the action of sleep can be more sophisticated than simply strengthening and stabilizing memories. It can lead to the selective retention of emotional memories, or even of emotional components of a scene, while allowing other memories and parts of a scene to fade. It can enhance our ability to extract the gist from a list of words, or the rules governing a complex probabilistic game. It can lead to insights ranging from finding the single word that logically connects three apparently unrelated words, to discovering an unexpected rule that allows for the more efficient solving of mathematical problems. It can facilitate the integration of new information into existing networks of related information. And it has been shown to help infants gain language skills. Disruptions of normal sleep in neurologic and psychiatric disorders can lead to a failure of these processes.
As we describe in our upcoming book When Brains Dream, dreams appear to be part of this ongoing memory processing, and their occurrence and content can predict subsequent memory improvement. While there is a vigorous debate over whether the actual conscious experiencing of dreams while they occur serves a function, we believe that it does, and that it is similar to that proposed for waking consciousness. Antonio Damasio, in this 2000 book The Feeling of What Happens, argues that consciousness provides two critical functions to the human brain: to construct narratives and to feel one’s emotional response to them. Together, they give humans (and presumably other conscious animals) the ability to imagine possibilities, evaluate them, and thereby plan future actions. Our NEXTUP model of dreaming (Network Exploration to Understand Possibilities) proposes that dreaming serves a similar function.
Specifically, we argue that dreaming allows the sleeping brain to enter an altered state of consciousness in which it can construct imagined narratives and respond emotionally to them. While dreaming, the brain identifies associations between recently formed memories (typically from the preceding day) and older, often only weakly related memories, and monitors whether the narrative it constructs from these memories induces an emotional response in the brain. If an emotional feeling is detected, the brain tags the association as potentially valuable, strengthening the link between the two memories and making the association available during subsequent wakefulness.
But dreaming is different from waking consciousness. First, the dreaming brain cannot access and incorporate complete episodic memories (i.e., memories of actual events in our lives), so the associative exploration of dreams is limited to semantic and nondeclarative memories (i.e., memories related to general world knowledge and those acquired and used unconsciously, respectively). In other words, while imagining and planning during wakefulness is normally based on recalled events, narrative construction during dreaming is based on semantic associations of these events, giving dreams their metaphorical quality and allowing for a more expansive investigation of associative links.
Second, the neurochemical modulation of the brain is altered during sleep, and especially during rapid eye movement (REM) sleep, when the release of norepinephrine and serotonin in the brain is shut off while levels of acetylcholine reach their peak in regions such as the hippocampus. These shifts bias memory networks toward the activation of normally weak associations, perhaps explaining the bizarreness of many dreams, especially during REM sleep.
Third, REM sleep is accompanied by a general activation of the limbic system, presumably explaining the enhanced emotionality seen in REM dreams, while also biasing the brain toward creating emotional responses to imagined dream narratives.
Finally, unlike problem solving during wakefulness that relies on imagining and planning, dreaming stops short of offering definitive solutions to our current concerns. Instead, our dreams serve to explore the solution space, helping us to discover new possibilities. It is up to other processes, both in wakefulness and sleep, to draw conclusions and delineate our plans. Dreaming takes what has been and shows us what might be.
Robert Stickgold is a professor at Harvard Medical School and director of the Center for Sleep and Cognition. Antonio Zadra is a professor at the Université de Montréal and a researcher at the Center for Advanced Research in Sleep Medicine. Read an excerpt of When Brains Dream.