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Sugary handshakes are how cells talk to each other − understanding these name tags can clarify how the immune system works



Sugary handshakes are how cells talk to each other − understanding these name tags can clarify how the immune system works

Handshakes between glycans are one way cells recognize each other.
Kelvin Anggara, CC BY

Kelvin Anggara, Max Planck Institute for Solid State Research

Like the people they make up, cells communicate by bumping into one another and exchanging handshakes. Unlike people, cells perform these handshakes using the diverse range of sugar molecules coating their surface like trees covering a landscape. Handshakes between these sugar molecules, or glycans, trigger cells to react in specific ways toward each other, such as escape, ignore or destroy.

Figuring out the “body language” of glycans during these handshakes can clues to how cancers, infections and immune work, as well as to and sustainability challenges society faces today.

What are glycans?

Each glycan molecule is made up of a network of individual sugar molecules bonded together. The vast number of possible glycan structures that can be built from connecting these sugar molecules together allows glycans to store rich information.

Because all living cells are covered with sugars, glycans act like ID cards for cells. They display the cell's identity, such as whether it's a bacteria or human cell, and its state, such as whether it's healthy or cancer, to the rest of the body and allow other cells to recognize and respond to it. For example, these identifying signs allow our immune cells to recognize and clear out harmful bacteria and cancerous cells while leaving healthy cells in peace.


An example of how glycan-stored information is important to daily life is your blood type. Glycans are chemically bonded to proteins and lipids on the surface of red blood cells. Notably, the surface of type A red blood cells have glycans that differ from the glycans on the surface of type B and type O red blood cells. Knowing what blood type you have is important to avoid an unwanted immune response during blood transfusions.

Diagram showing the glycan structures of types A, B and O red blood cells
Your blood type is determined by the types of glycans, depicted here in circles and triangles, on your red blood cells.
Kelvin Anggara/Created with BioRender.com, CC BY-SA

Proteins decorated with glycans, or glycoproteins, and lipids decorated with glycans, or glycolipids, are ubiquitous in nature.

For example, distinctive glycoproteins cover the surface of the viruses that cause COVID-19, HIV and H1N1 influenza and help them infect cells. Glycolipids also coat many bacteria, allowing them to stick to their hosts and protect them from viruses and immune cells.

More recently, researchers discovered pieces of genetic material decorated with glycans on the surfaces of mammalian cells, challenging the long-standing notion that genetic material could be found only in the nucleus of cells and launching research to determine the functions of these glycans. One recent study showed that these molecules are vital in attracting immune cells toward infected or tissues.

How do cells read glycans?

In addition to the rich biological information contained in glycans, their easily accessible locations on cell surfaces make them highly attractive targets in scientific research and drug .


Cells sense glycans on the surfaces of other cells by using proteins called lectins, among others. Each lectin has a unique area that allows it to bind to glycans with a specific matching sequence, triggering complex signals that to a biological action.

For example, a subfamily of lectins called C-type lectins are able to recognize the specific glycans on the outer walls of harmful viruses, fungi and bacteria. Found on surfaces of certain immune cells, these lectins deliver the glycans to proteins on other immune cells that can now selectively destroy any viruses or cells that carry that glycan. This allows the immune system to clear the body of harmful pathogens. For example, these lectins recognize glycans on the surfaces of cancer cells and direct other immune cells to eliminate these cancer cells.

Illustration of a spherical influenza virus, with red and blue spikes studding its surface
The spikes on the surface of the influenza virus are composed of glycoproteins.
Dr_Microbe/iStock via Getty Images Plus

Another type of lectin called siglecs are found on surfaces of immune cells and help them distinguish self from nonself, that is, between the cells that make up the body and the cells that are foreign to the body. Because siglecs are involved in controlling how the immune system responds to many cancers, allergies, autoimmune diseases and neurodegeneration, they offer an opportunity to treat these conditions.

The early success of glycan-based drugs is exemplified by Pfizer's Prevnar vaccine to prevent bacterial pneumonia, which was approved by the Food and Drug Administration in 2010. Prevnar contains glycans from various strains of Streptococcus pneumoniae, the leading cause of bacterial pneumonia in children and adults. The bacterial glycans in the vaccine trigger an immune response when immune cells recognize the glycans as foreign threats. Once immune cells learn how to neutralize the threat, the body becomes immune to future invasion by bacteria with the same glycans.

Examining every sugar molecule

Because scientists are still unable to extract all the biological information in glycans, their full potential as treatments has remained untapped. Comprehensively extracting all the information stored in glycans is very difficult because there isn't currently technology able to analyze the complex and diverse structures of glycans. Researchers still don't know what these “sugar codes” look like and how they function.


Individual glycans are composed of sugar molecules in unique arrangements, but current analytical tools can only simultaneously analyze many glycans. To see why this is a problem for analysis, imagine all the glycans in a cell as candies in a jar. Some of them are the same colors and some are not. It would be difficult to identify and quantify the color of every candy in the jar if you're unable to pour them out to individually sort through each one of them.

Jar of colorful candy on a table
Can you identify the color of every candy and count how many there are of each color without opening the jar?
Clem Onojeghuo/Unsplash, CC BY-SA

My lab is confronting this by developing imaging technology that can analyze the structure of glycans by imaging each individual molecule. Essentially, we're developing a technique to open the jar and study every single candy one at a time.

In the long , my team aspires to unveil how these glycans present themselves to the proteins that recognize them and, finally, reveal the very language that cells use to express themselves.The Conversation

Kelvin Anggara, Group leader in Single molecule imaging, Max Planck Institute for Solid State Research

This article is republished from The Conversation under a Creative Commons license. Read the original article.


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Early COVID-19 research is riddled with poor methods and low-quality results − a problem for science the pandemic worsened but didn’t create



Early COVID-19 research is riddled with poor methods and low-quality results − a problem for science the pandemic worsened but didn't create

The pandemic spurred an increase in research, much of it with methodological holes.
Andriy Onufriyenko/Moment via Getty Images

Dennis M. Gorman, Texas A&M University

Early in the COVID-19 pandemic, researchers flooded journals with studies about the then-novel coronavirus. Many publications streamlined the peer-review for COVID-19 papers while keeping acceptance rates relatively high. The assumption was that policymakers and the public would be able to identify valid and useful research among a very large volume of rapidly disseminated information.

However, in my review of 74 COVID-19 papers published in 2020 in the top 15 generalist public journals listed in Google Scholar, I found that many of these studies used poor quality methods. Several other reviews of studies published in medical journals have also shown that much early COVID-19 research used poor research methods.

Some of these papers have been cited many times. For example, the most highly cited public health publication listed on Google Scholar used data from a sample of 1,120 people, primarily well-educated young women, mostly recruited from social over three days. Findings based on a small, self-selected convenience sample cannot be generalized to a broader population. And since the researchers ran more than 500 analyses of the data, many of the statistically significant results are likely chance occurrences. However, this study has been cited over 11,000 times.

A highly cited paper means a lot of people have mentioned it in their own work. But a high number of citations is not strongly linked to research quality, since researchers and journals can and manipulate these metrics. High citation of low-quality research increases the chance that poor evidence is being used to inform policies, further eroding public confidence in science.


Methodology matters

I am a public health researcher with a long-standing interest in research quality and integrity. This interest lies in a belief that science has helped solve important social and public health problems. Unlike the anti-science movement spreading misinformation about such successful public health measures as vaccines, I believe rational criticism is fundamental to science.

The quality and integrity of research depends to a considerable extent on its methods. Each type of study design needs to have certain features in order for it to valid and useful information.

For example, researchers have known for decades that for studies evaluating the effectiveness of an intervention, a control group is needed to know whether any observed effects can be attributed to the intervention.

Systematic reviews pulling together data from existing studies should describe how the researchers identified which studies to include, assessed their quality, extracted the data and preregistered their protocols. These features are necessary to ensure the review will all the available evidence and tell a reader which is worth attending to and which is not.


Certain types of studies, such as one-time surveys of convenience samples that aren't representative of the target population, collect and analyze data in a way that does not allow researchers to determine whether one variable caused a particular outcome.

Systematic reviews involve thoroughly identifying and extracting information from existing research.

All study designs have standards that researchers can consult. But adhering to standards slows research down. a control group doubles the amount of data that needs to be collected, and identifying and thoroughly reviewing every study on a topic takes more time than superficially reviewing some. Representative samples are harder to generate than convenience samples, and collecting data at two points in time is more work than collecting them all at the same time.

Studies comparing COVID-19 papers with non-COVID-19 papers published in the same journals found that COVID-19 papers tended to have lower quality methods and were less likely to adhere to reporting standards than non-COVID-19 papers. COVID-19 papers rarely had predetermined hypotheses and plans for how they would report their findings or analyze their data. This meant there were no safeguards against dredging the data to find “statistically significant” results that could be selectively reported.

Such methodological problems were likely overlooked in the considerably shortened peer-review process for COVID-19 papers. One study estimated the average time from submission to acceptance of 686 papers on COVID-19 to be 13 days, compared with 110 days in 539 pre-pandemic papers from the same journals. In my study, I found that two online journals that published a very high volume of methodologically weak COVID-19 papers had a peer-review process of about three weeks.


Publish-or-perish culture

These quality control issues were present before the COVID-19 pandemic. The pandemic simply pushed them into overdrive.

Journals tend to favor positive, “novel” findings: that is, results that show a statistical association between variables and supposedly identify something previously unknown. Since the pandemic was in many ways novel, it provided an for some researchers to make bold claims about how COVID-19 would spread, what its effects on mental health would be, how it could be prevented and how it might be treated.

Person with head in hands, elbows planted on stacks of paperwork and books littering a desk, glasses and laptop on the side
Many researchers feel pressure to publish papers in order to advance their careers.
South_agency/E+ via Getty Images

Academics have worked in a publish-or-perish incentive system for decades, where the number of papers they publish is part of the metrics used to evaluate employment, promotion and tenure. The flood of mixed-quality COVID-19 information afforded an opportunity to increase their publication counts and boost citation metrics as journals sought and rapidly reviewed COVID-19 papers, which were more likely to be cited than non-COVID papers.

Online publishing has also contributed to the deterioration in research quality. Traditional academic publishing was limited in the quantity of articles it could generate because journals were packaged in a printed, physical document usually produced only once a month. In contrast, some of today's online mega-journals publish thousands of papers a month. Low-quality studies rejected by reputable journals can still find an outlet happy to publish it for a fee.

Healthy criticism

Criticizing the quality of published research is fraught with risk. It can be misinterpreted as throwing fuel on the raging fire of anti-science. My response is that a critical and rational approach to the production of knowledge is, in fact, fundamental to the very practice of science and to the functioning of an open society capable of solving complex problems such as a worldwide pandemic.


Publishing a large volume of misinformation disguised as science during a pandemic obscures true and useful knowledge. At worst, this can to bad public health practice and policy.

Science done properly produces information that allows researchers and policymakers to better understand the world and test ideas about how to improve it. This involves critically examining the quality of a study's designs, statistical methods, reproducibility and transparency, not the number of times it has been cited or tweeted about.

Science depends on a slow, thoughtful and meticulous approach to data collection, analysis and presentation, especially if it intends to provide information to enact effective public health policies. Likewise, thoughtful and meticulous peer review is unlikely with papers that appear in print only three weeks after they were first submitted for review. Disciplines that reward quantity of research over quality are also less likely to protect scientific integrity during crises.

Two scientists pipetting liquids under a fume hood, with another scientist in the background examining a sample
Rigorous science requires careful deliberation and attention, not haste.
Assembly/Stone via Getty Images

Public health heavily draws upon disciplines that are experiencing replication crises, such as psychology, biomedical science and biology. It is similar to these disciplines in terms of its incentive structure, study designs and analytic methods, and its inattention to transparent methods and replication. Much public health research on COVID-19 shows that it suffers from similar poor-quality methods.

Reexamining how the discipline rewards its scholars and assesses their scholarship can help it better prepare for the next public health crisis.The Conversation

Dennis M. Gorman, Professor of Epidemiology and Biostatistics, Texas A&M University


This article is republished from The Conversation under a Creative Commons license. Read the original article.

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Making the moral of the story stick − a media psychologist explains the research behind ‘Sesame Street,’ ‘Arthur’ and other children’s TV



Making the moral of the story stick − a media psychologist explains the research behind ‘Sesame Street,' ‘Arthur' and other children's TV

Children's TV shows are typically designed to improve their viewers' cognitive, social and moral .
U.S. Air Force photo by Staff Sgt. Scott Saldukas/Released via Flickr

Drew Cingel, University of California, Davis; Allyson Snyder, University of California, Davis; Jane Shawcroft, University of California, Davis, and Samantha Vigil, University of California, Davis

To adult viewers, educational content for children, such as “Sesame Street” or “Daniel Tiger's Neighborhood,” may seem rather simplistic. The pacing is slow, key themes are often repeated and the visual aspects tend to be plain.

However, many people might be surprised to learn about the sheer amount of research that goes into the design choices many contemporary programs use.

For more than a decade, I have studied just that: how to design media to children's learning, particularly in moral development. My research, along with the work of many others, shows that children can learn important developmental and social skills through media.

History of research on children's media

Research on how to design children's media to support learning is not new.


When “Sesame Street” debuted in November 1969, it began a decadeslong practice of testing its content before airing it to ensure children learned the intended messages of each episode and enjoyed watching it. Some episodes included messages notoriously difficult to teach to young children, lessons about , divorce and racism.

Researchers at the Sesame Workshop hold focus groups at local preschools where participating children watch or interact with Sesame content. They test the children on whether they are engaged with, pay attention to and learn the intended message of the content. If the episode passes the test, then it moves on to the next stage of production.

Puppeteer holding muppet Abby Cadabby out for a child to engage with
The Sesame Workshop uses muppets to teach children about difficult topics.
AP Photo/Bebeto Matthews

If children do not learn the intended message, or are not engaged and attentive, then the episode goes back for editing. In some cases, such as a 1992 program designed to teach children about divorce, the entire episode is scrapped. In this case, children misunderstood some key information about divorce. “Sesame Street” did not include divorce in its content until 2012.

Designing children's media

With from the pioneering research of “Sesame Street,” along with research from other children's television shows both in the industry and in academia, the past few decades have seen many new insights on how best to design media to promote children's learning. These strategies are still shaping children's shows .

For example, you may have noticed that some children's television characters speak directly to the camera and pause for the child viewer at home to yell out an answer to their question. This design strategy, known as participatory cues, is famously used by the shows “Blue's Clues” and “Dora the Explorer.” Researchers found that participatory cues in TV are linked to increased vocabulary learning and content comprehension among young children. They also increase children's engagement with the educational content of the show over time, particularly as they learn the intended lesson and can give the character the correct answer.

Participatory cues are a prominent feature of children's shows like ‘Blues Clues.'

You may have also noticed that children's media often features jokes that seem to be aimed more at adults. These are often commentary about popular culture that require context children might not be aware of or involve more complex language that children might not understand. This is because children are more likely to learn when a supportive adult or older sibling is watching the show alongside them and helping explain or connect it to the child's . Known as active mediation, research has shown that talking about the goals, emotions and behaviors of media characters can help children learn from them and even improve aspects of their own emotional and social development.

Programs have also incorporated concrete examples of desired behaviors, such as treating a neurodiverse character fairly, rather than discussing the behaviors more abstractly. This is because children younger than about age 7 struggle with abstract thinking and may have difficulty generalizing content they learned from media and applying it to their own lives.

Research on an episode of “Arthur” found that a concrete example of a main character experiencing life through the eyes of another character with Asperger's syndrome improved the ability of child viewers to take another person's perspective. It also increased the nuance of their moral judgments and moral reasoning. Just a single viewing of that one episode can positively influence several aspects of a child's cognitive and moral development.

Teaching inclusion through media

One skill that has proven difficult to teach children through media is inclusivity. Multiple studies have shown that children are more likely to exclude others from their social group after viewing an episode explicitly designed to promote inclusion.


For example, an episode of “Clifford the Big Red Dog” involved Clifford and his moving to a new town. The townspeople initially did not want to include Clifford because he was too big, but they eventually learned the importance of getting to know others before making judgments about them. However, watching this episode did not make children more likely to play with or view disabled or overweight children favorably.

Based on my own work, I argue that one reason inclusivity can be difficult to teach in children's TV may be due to how narratives are structured. For example, many shows actually model antisocial behaviors during the first three-quarters of the episode before finally modeling prosocial behaviors at the end. This may inadvertently teach the wrong message, because children tend to focus on the behaviors modeled for the majority of the program.

My team and I conducted a recent study showing that including a 30-second clip prior to the episode that explains the inclusive message to children before they view the content can help increase prosocial behaviors and decrease stigmatization. Although this practice might not be common in children's TV at the moment, adult viewers can also fill this role by explaining the intended message of inclusivity to children before watching the episode.

Smiling parent sitting with two children watching TV together
Adult viewers watching TV alongside children can help kids apply the lessons the shows teach to their own lives.
miniseries/E+ via Getty Images

Parenting with media

Children's media is more complex than many people think. Although there is certainly a lot of media out there that may not use study-informed design practices, many shows do use research to ensure children have the best chance to learn from what they watch.

It can be difficult to be a parent or a child in a media-saturated world, particularly in deciding when children should begin to watch media and which media they should watch. But there are relatively simple strategies and supportive adults can use to leverage media to support their child's healthy development and future.


Parents and other adults can help children learn from media by watching alongside them and answering their questions. They can also read reviews of media to determine its quality and age appropriateness. Doing so can help children consume media in a healthy way.

We live in a media-saturated world, and restricting young children's media use is difficult for most families. With just a little effort, parents can model healthy ways to use media for their children and select research-informed media that promotes healthy development and well-being among the next generation.The Conversation

Drew Cingel, Associate Professor of Communication, University of California, Davis; Allyson Snyder, Ph.D. Candidate in Communication, University of California, Davis; Jane Shawcroft, Ph.D. Candidate in Communication, University of California, Davis, and Samantha Vigil, Ph.D. Candidate in Communication, University of California, Davis

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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War in Ukraine at 2 years: Destruction seen from space – via radar



War in Ukraine at 2 years: Destruction seen from space – via radar

Satellite radar data shows the complete destruction of the Ukrainian of Bakhmut.
Xu et al. (2024), CC BY-NC-ND

Sylvain Barbot, USC Dornsife College of Letters, Arts and Sciences

As soldiers and citizens provide information from the front lines and affected areas of the war in Ukraine – two years old as of Feb. 24, 2024 – in quasi-real time, an active open-source intelligence community has formed to keep track of troop activity, destruction and other aspects of the war.

Remote sensing complements this approach, offering a safe means to study inaccessible or dangerous areas. For example, seismologists have documented the high pace of bombardments and firing of artillery around Kyiv during the first few months of the war.

Previously, Teng Wang, a professor at the Peking in China, and I – both Earth scientists – studied illegal nuclear tests in North Korea with satellite data.

Putting our skills to good use once again, we, with graduate student Hang Xu, have analyzed the development of the war from space. We exclusively used open-source, freely accessible data to ensure that all our findings could be reproduced, guaranteeing transparency and neutrality.


View from above

Sensors on satellites record electromagnetic waves radiated or reflected from Earth's surface with wavelengths ranging from hundreds of nanometers to tens of centimeters, enabling semi-continuous monitoring on a global scale, unimpeded by political boundaries and natural obstacles.

Optical images, the equivalent of photographs taken from , governments, researchers and journalists monitor troop movements on the front and the destruction of equipment and facilities. Although optical images are easily interpreted, they suffer from cloud and operate only during daylight.

To counter these issues, we used radars onboard satellites. Space-borne radar systems beam long-wavelength electromagnetic waves toward the Earth and then record the returning echos. These waves – about 0.4 to 4 inches (1 to 10 centimeters) – can penetrate clouds and smoke. Radar interferometry has already proved to be an invaluable tool to monitor widespread caused by natural disasters.

a pair of satellite views showing the same section of a city, one with intact buildings and green space and the other damaged or destroyed buildings and charred earth
Satellite photography like these ‘before' and ‘after' images can provide a visceral sense of the destruction in the war in Ukraine.
Satellite image (c) 2023 Maxar Technologies via Getty Images

Radar from space

and publicly available radar data for civilian applications is rare – the United States is to launch its first one in March 2024 – but the European Space Agency has made such data available since the early 1990s. Data from the European Space Agency's Sentinel-1 satellite radar is freely accessible via their data hub.

Two radar images formed over the same area can be used to detect changes to structures and other surfaces. Interferometry measures the difference in travel time between two radar signals, which is a measure of change in the shape or position of surfaces. Another measure of surface change is the coherence of the reflected – that is, the degree of similarity between two different images when comparing neighboring pixels at the same position in the two images. A large coherence implies little change and thus the preservation of a building or other structure. On the other hand, a loss of coherence in the context of a battlefield implies damage or destruction of a building or structure.


Sentinel-1 radar's spatial resolution of 66 feet (20  meters) over a swath of 255 miles (410  kilometers) combined with 12-day updates makes its radar data ideal for monitoring urban warfare. Previous research efforts have used satellite radar data to assess damage in Kyiv and Mariupol. We used the data to analyze the evolution of damage to over time during several lengthy battles.

four maps of a city with increasing amounts of the buidlings marked in red
Changes in radar data during the battle of Bahkmut show increasing amounts of destruction. Red pixels imply damaged or destroyed buildings.
Xu et al. (2024), CC BY-NC-ND

Measure of destruction

We flagged highly damaged areas by comparing radar coherence before and after the war, within the areas classified as artificial surfaces by the European Space Agency's WorldCover 2021 dataset. Using this approach, we first analyzed the battle of Bakhmut, one of the longest and bloodiest of the war, which began on Oct. 8, 2022, and ended with a Russian victory on May 20, 2023.

When Hang Xu showed Teng Wang and me the data he had processed, we were puzzled. We saw a checkerboard pattern all over the city. We quickly realized the horror of the situation. The only thing that survived after the yearlong battle was the network of roads in the city. All buildings had partially or completely collapsed due to the continuous bombardment.

We then took a look at the battles of Rubizhne, Sievierodonetsk and Lysychansk that started in April 2022 and ended with a Russian victory on July 2, 2022. The comparatively lower destruction of Lysychansk is explained by the rapid encirclement of the city from the south instead of continued frontal assaults, as was the case in Bakhmut. The radar data reveals destruction away from the front line within cities, showing the whole extent of the devastation.

four maps of a set of three cities with increasing amounts of the buidlings marked in red
Changes in radar data during the battles of Rubizhne, Sievierodonetsk and Lysychansk show increasing amounts of destruction. Urban areas are shown in gray with damage in red.
Xu et al. (2024), CC BY-NC-ND

Devastation in focus

Remote sensing images offer the means to safely monitor the impact of armed conflicts, particularly as high-intensity wars in urban environments proliferate. Open-access satellite instruments complement other forms of open-source intelligence by offering unimpeded access to high-resolution, unbiased information, which can help people grasp the true impact of war on the ground.

The picture is clear: The real story of war is destruction.The Conversation

Sylvain Barbot, Associate Professor of Earth Sciences, USC Dornsife College of Letters, Arts and Sciences


This article is republished from The Conversation under a Creative Commons license. Read the original article.

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