Study finds high prevalence of COVID-19 and flu co-infections during 2021-2022 flu season

Differences discovered in co-infection prevalence between Delta and Omicron variants

Peer-Reviewed Publication

UNIVERSITY OF MISSOURI-COLUMBIA

Researchers from the University of Missouri School of Medicine have discovered a high prevalence of COVID-19 co-infections in central Missouri during the 2021-2022 flu season, with a monthly co-infection rate as high as 48% among individuals with COVID-19.  

The findings come from 462 patients at University of Missouri Health Care who tested positive for COVID-19 and were subsequently tested for influenza. Of those who tested positive for COVID-19, 33% also tested positive for the flu.  

“Co-infection in our samples peaked in October 2021 at 48% when the Delta variant was dominant, and reached the lowest point at 7.1% in January 2022 when the Omicron variant prevailed,” said senior author Henry Wan, PhD, professor of Molecular Microbiology and Immunology, Veterinary Pathobiology, Electrical Engineering and Computer Science. Wan also directs the NextGen Center for Influenza and Emerging Infectious Diseases and is a primary investigator at the Bond Life Sciences Center. 

Of the 462 patients infected with COVID-19, 51% had the Delta variant, while 38% had the Omicron variant. Those who were infected with the Omicron variant and those who received at least one influenza vaccine during the 2020-2022 influenza seasons were less likely to become co-infected with both the flu and COVID-19. They were also less likely to become hospitalized. 

“Despite low flu vaccine effectiveness for the 2021-2022 season, which was estimated at less than 16%, our study highlights the importance of influenza vaccinations, as they appear to not only offer some protection against influenza infections but importantly, against COVID-19 and flu co-infections,” Wan said.  

Future studies involving a wider geographic area and a more diverse population will be needed to provide more clarity on the prevalence of overall flu and COVID-19 co-infections and the effectiveness of both COVID-19 and flu vaccines.  

“Testing for both flu and COVID-19 viruses in patients experiencing symptoms of respiratory illness and vaccinations against both viruses should continue to be encouraged,” Wan said. 

 In addition to Wan, the study authors include MU colleagues Cynthia Tang, a MD/PhD student; Maria Boftsi, PhD, postdoctoral research fellow; Lindsay Staudt, medical student and research specialist; Sabrina Duong, a medical student; Jane McElroy, PhD, professor of family and community medicine; Adrienne Ohler, PhD, associate research professor; Detlef Ritter, MD, professor of clinical pathology; and Richard Hammer, MD, professor of pathology. 

Their study, “SARS-CoV-2 and influenza co-infection; a cross sectional study in central Missouri during the 2021-2022 influenza season,” was recently published in the journal Virology.  

This work was supported by the National Institutes of Health. The authors disclose no conflicts of interest. 

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JOURNAL

Virology

DOI

10.1016/j.virol.2022.09.009 

METHOD OF RESEARCH

Meta-analysis

SUBJECT OF RESEARCH

People

ARTICLE TITLE

SARS-CoV-2 and influenza co-infection: A cross-sectional study in central Missouri during the 2021–2022 influenza season

ARTICLE PUBLICATION DATE

1-Nov-2022

CItyU researchers invent smart mask to track respiratory sounds for respiratory disease identification

Peer-Reviewed Publication

CITY UNIVERSITY OF HONG KONG

 

VIDEO: NANOCOMPOSITE-SENSOR INTEGRATED SMART MASK ALLOWS THE DETECTION OF A WIDE-BANDWIDTH DYNAMIC PRESSURE RANGE WITH HIGH SENSITIVITY FOR TRACKING MULTIPHASE RESPIRATORY ACTIVITY. view more 

CREDIT: WILEY EDITING SERVICES / DOI: 10.1002/ADVS.202203565

Wearing face masks has been recognised as one of the most effective ways to prevent the spread of COVID-19, even in its coming endemic phase. Apart from the conventional function of masks, the potential for smart masks to monitor human physiological signals is being increasingly explored. A research team led by the City University of Hong Kong (CityU) recently invented a smart mask, integrating an ultrathin nanocomposite sponge structure-based soundwave sensor, which is capable of detecting respiratory sounds of breathing, coughing and speaking.

Using machine-learning algorithms and a high sensitivity soundwave sensor operable across a wide bandwidth, the smart mask has opened new avenues for its application in the identification of respiratory diseases, as well as a voice interaction tool. This ultra-lightweight wearable technology also has the potential to improve personal and public health by enabling prolonged and systematic respiratory health monitoring in daily life.

A research team led by Professor Li Wenjung, Chair Professor in the Department of Mechanical Engineering (MNE), Professor Wang Jianping, Professor in the Department of Computer Science (CS), and Dr Yu Xinge, Associate Professor in the Department of Biomedical Engineering (BME) at CityU, recently developed this smart mask, which can detect and distinguish multiple respiratory actions. Professor Shen Jiangang’s team from the School of Chinese Medicine of The University of Hong Kong also made an important contribution to the project. The findings were published in Advanced Science under the title “Wide-bandwidth nanocomposite-sensor integrated smart mask for tracking multiphase respiratory activities”.

Importance of wearing masks even if COVID-19 becomes endemic

“Many countries now believe that COVID-19 will soon become endemic,” said Professor Li. “However, we must set aside optimism and be realistic about the likely levels of illness, disability and death associated with this disease in the coming years. It is important to remember that endemicity does not correspond to harmlessness.” He used malaria as an example to illustrate that even though it is currently considered endemic in 87 countries, in 2020, it infected an estimated 241 million people and caused 627,000 deaths, according to the World Health Organization. Thus, he suggested that people should continue to be cautious about COVID-19 and use available and proven measures, including masks, to control the spread of the virus.

“This smart mask utilises our self-developed, high-sensitivity, wide-bandwidth flexible sensor that can detect and record daily human respiratory activity, such as breathing, coughing and speaking for cloud data storage,” explained Professor Li.

The smart mask developed by the team has a sponge-like structure as thin as 400μm, fabricated with carbon nanotube and polydimethylsiloxane (CNT/PDMS) materials, using the team’s novel modified sacrificial-release technique. The ultra-thin, lightweight sensor can be practically integrated and work effectively with both rigid masks and deformable non-woven fabric masks.

Good performance in static and dynamic pressure

The research team recruited 31 people in order to collect their respiratory activity while they wore the smart mask. The findings showed that the acoustic wave sensor was highly sensitive in measuring both static and dynamic pressure. Besides performing well in the static pressure range of 27.9 Pa – 2.5 kPa, the sensor also responded to high-frequency dynamic pressure generated by the human voice, i.e., sound harmonic acoustic energy up to 4000 Hz.  In addition, the sensor can sense air movement, including directional flow and vibration. These findings suggest that the sensor could be used to detect human respiratory activity by integrating it with a commercial polycarbonate mask. It also demonstrated that the smart mask could detect and differentiate three common respiratory functions: breathing, coughing and speaking.

“Advanced artificial intelligence technology enables the integrated mask to recognise different coughing and breathing patterns automatically, indicating its potential use to diagnose respiratory-related diseases in the future,” said Professor Wang. “Presently, researchers use commercial sensors to detect temperature changes and airflow to count the number of coughs, but they cannot capture important physiological information contained in the human voice, coughing and breathing. Our smart mask is sensitive to both subtle air pressure and high-frequency vibrations and can detect three phrases of coughing,” added Professor Li.

The team aims to eventually develop real-time diagnostics algorithms for applications such as pneumoconiosis symptom assessment. “As a potentially low-cost, daily smart wearable device, this new IoT smart mask will help personal and public health management of respiratory disease screening and diagnosis, especially in cities with a dense population, like Hong Kong,” said Dr Yu. The speech-detection ability of the smart mask can also help resolve the sound attenuation problem caused by wearing masks.

The first co-authors of the paper are Miss Suo Jiao, Mr Liu Yifan and Dr Wu Cong, all of whom are Professor Li’s students. Corresponding co-authors include Dr Yu, Professor Wang and Professor Li from CityU. Other team members from CityU include Dr Walid Daoud and Dr Yang Zhengbao from the MNE and Dr Li Xinyue from the School of Data Science.

The research was supported by the Shenzhen Municipality Science and Technology Innovation Commission, the Hong Kong Research Grants Council, and the Hong Kong Centre for Cerebro-cardiovascular Health Engineering.

(From left) Professor Wang Jianping, Professor Li Wenjung, and Suo Jiao, PhD student in the Department of Mechanical Engineering at City University of Hong Kong.

City University of Hong Kong’s smart mask will help improve personal and public health.

The flexible sensor can be used to detect human respiratory activity by integrating it with commercial masks.

Illustration of the overall concept of the smart mask, which integrates an ultra-thin nanocomposite soundwave sensor to detect various respiratory sounds of breathing, coughing and speaking.

CREDIT

City University of Hong Kong

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JOURNAL

Advanced Science

DOI

10.1002/advs.202203565 

METHOD OF RESEARCH

Experimental study

SUBJECT OF RESEARCH

Not applicable

ARTICLE TITLE

Wide-Bandwidth Nanocomposite-Sensor Integrated Smart Mask for Tracking Multiphase Respiratory Activities

The era of digital olfaction science is now – the smell of digital will be highlighted during the 7th International Meeting of the Digital Olfaction Society this November in Tokyo

Meeting Announcement

MITOCHONDRIA-MICROBIOTA TASK FORCE

 

IMAGE: SPEAKERS OF THE 7TH DOS ANNUAL MEETING view more 

CREDIT: CREDITS TO THE DIGITAL OLFACTION SOCIETY

The 7th International Meeting of the Digital Olfaction Society (DOS) will take place on November 29-30 at Tokyo, Japan, and Online. This meeting is headed by Prof. Jesús Lozano Rogado, President of DOS, University of Extremadura, Spain.

 

DOS Displaying & Demonstrations

During the 7th DOS Annual Meeting, several demonstrations will be displayed. Each team will have a dedicated space to show, demonstrate, explain and discuss their project.

Among the DOS 2022 Demonstrations:

Demonstration by DOS President

Jesus Lozano Rogado, President of DOS, University of Extremadura, Spain

Brand New Olfactive Age: Olfactive Technologies for Olfactory Measurement and Testing

Shuji Fujita, Sony Corporation Olfactory Business Development Office, Japan

Digital Olfaction Innovation by RICOH

Katsuya Ujimoto, Ricoh Company, Ltd., Japan

Demonstration of Aroma Oil Recognition by Deepsniffer

Chuanjun Liu, U.S.E. Co., Ltd, Japan

You are also invited to present your innovations and products in the olfaction and digital olfaction world. More information.

Program of the meeting.

 

Industrials attending the DOS 2022 Meeting:

Sony, Ricoh Company, ALPHA-MOS, Aroma Republic, Aromyx, Aryballe, GEMFluidix, International Flavors & Fragrances, LG Japan Lab, Moodify, Olfasense GmbH, Procter and Gamble, Sanyo Chemical Industries, Sentech GMI, Suntory Global Innovation Center, TAKASAGO, U.S.E. Co. Ltd. and others.

Among DOS 2022 Supporters: Sony Corporation, Ricoh Company.

 

Check all attendees.

 

About the Digital Olfaction Society

The aim of DOS is to create devices which not only can record smells, turn them into digital data but also transmit and restitute them where we like. The objective of DOS is also to gather, share, and complete the knowledge recently established about olfactory digitization. Our perspective is to build up constructive links between leading researchers and industrialists in order to set up appropriate strategies in order to implement Research & Development through practical applications with a high impact on our lifestyle thanks to the potential of olfactory digitization. We want to move from the Stone Age of odorous substance toward a New Age by means of digital fragrance, aroma and smell technologies.

DAYMARES

Daytime sleep enhance fear memories of emotional trauma and anxiety

New research will help shape strategies for the rehabilitation of people with anxiety disorders

Peer-Reviewed Publication

URAL FEDERAL UNIVERSITY

 

IMAGE: AS YURI PAVLOV SAYS, THE FEAR REACTION WAS STUDIED USING ELECTROENCEPHALOGRAPHY. view more 

CREDIT: NADEZHDA PAVLOVA

Scientists from the Ural Federal University (UrFU) and the University of Tübingen (Germany) studied the effect of sleep on the formation and consolidation of fear memory into long-term memory. The neuroscientists have found that a short nap enhances the memory for disturbing and fearful events, but a similar effect of enhancing memory was also observed after a period of wakefulness. The results of the study will be useful for developing strategies for the rehabilitation of people who have received emotional trauma during natural disasters, military operations, and acts of violence. The research published in Cognitive, Affective, & Behavioral neuroscience.

Memory consolidation is the transition of memories from short-term memory to long-term memory. It occurs primarily during sleep. Different studies show that sleeping after learning can have more positive effect than being passively awake. This happens through the reactivation of important memories, which may also be reflected in dreams. The positive effect of sleep can be observed even years later. However, at the moment there are no studies that investigated whether sleep enhances fear memory. The study tried to shed the light on the question what happens with fear memories after a period of sleep and wakefulness.

“Understanding the effect of sleep in situations where emotional trauma occurs is important for developing effective strategies for coping with disaster victims, people with panic or post-traumatic stress disorder. If we found that the effect of sleep on fear memory is similar to other types of memory, such as episodic memory (memory of life events), then it would be more beneficial for victims not to sleep after the trauma. In our experiments, we determined that a two-hour daytime nap reinforces the memories of fear learnt just before sleep. However, a similar effect was observed after wakefulness - watching an emotionally neutral movie or a computer gaming similarly enhances fear memories”, says Yuri Pavlov, co-author of the article, researcher at the laboratory of Neurotechnology of UrFU and the Institute of Medical Psychology and Behavioral Neurobiology at the University of Tübingen.

Before and after sleep, the participants went through a fear conditioning paradigm. The participants in the experiment first heard a neutral tone, and then it was always paired with a loud noise, another tone was never paired with the noise, says the scientist.

“After multiple pairings, the neutral stimulus evoked an equally strong emotional response on its own. Interestingly, people typically rate the loud noise as more unpleasant than even electric shocks, also often used in fear research. The comparison between tones paired with the highly aversive noise and the other tone - ‘safe’ cue – allowed to investigate neural processes behind fear learning. We found that the neural signatures of fear learning enhanced after a nap, and in equal measure after short rest” – explains Yuri Pavlov.

The fear conditioned responses were studied by electroencephalography before and after a 2-hour daytime nap or an equal period of wakefulness in 18 healthy young people. The researchers are now moving the study to the clinic, where they plan to test patients in a vegetative state and a minimally conscious state to determine how sleep will affect their levels of anxiety and the formation of fear memories. They also note that further study of the effect of a longer sleep period is needed.

Reference

Anxiety disorders, such as panic, post-traumatic stress disorder (PTSD), or specific phobias, occur in response to stress. They are characterized by a constant feeling of anxiety and fear, which can increase over time.

Memory consolidation is the process of transforming primary labile memories into a stable long-term form. Studies of declarative (memory for facts), episodic (memory for life events), and procedural (memory for skills) memory show that sleep after learning has a positive effect.

A person's sleep cycle is typically approximately 1.5 hours long. At night, people sleep from 4 to 6 cycles, during the day they rarely sleep for more than one full cycle.

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JOURNAL

Cognitive Affective & Behavioral Neuroscience

DOI

10.3758/s13415-022-01037-5 

ARTICLE TITLE

Fear memory in humans is consolidated over time independently of sleep

New model can detect long-COVID’s effects using simple, 2D chest X-rays

Peer-Reviewed Publication

UNIVERSITY OF IOWA

 

IMAGE: UNIVERSITY OF IOWA RESEARCHERS HAVE CREATED AN ADVANCED MODEL THAT CAN DETECT LUNG DAMAGE IN LONG-COVID PATIENTS USING A SIMPLE CHEST X-RAY. THE MODEL TAKES DATA POINTS FROM 2D LUNG IMAGES CONSTRUCTED FROM 3D CT LUNG SCANS. THIS IMAGE SHOWS DETAILS OF THE LUNG IN A 2D IMAGE. THE MODEL IS ATTRACTIVE, BECAUSE 2D CHEST X-RAY EQUIPMENT IS MORE COMMONLY AVAILABLE AND LESS COSTLY. view more 

CREDIT: CHING-LONG LIN LAB, UNIVERSITY OF IOWA

For patients dealing with lingering respiratory symptoms from the novel coronavirus, a chest X-ray can reveal only so much. The two-dimensional (2D) scans simply can’t distinguish compromised lung function. For that diagnosis, a more expensive, three-dimensional (3D) technique called a CT scan is necessary.

Yet many medical clinics in the United States don’t have CT scanning equipment, leaving so-called long-COVID patients with little information about their lung function.

That may change. In a new study, researchers at the University of Iowa have developed what is called a contrastive learning model. This model “learns” from composite 2D images constructed from 3D CT images to detect compromised lung function in long-COVID patients. Another technique, called transfer learning, then conveys lung diagnostic information from a CT scan to a chest X-ray, thus allowing chest X-ray equipment to detect abnormalities the same as if those patients had used a CT scan.

In the study, the researchers showed how their contrastive learning model could be applied to detect small airways disease, which is an early stage of compromised lung function in long-COVID patients. Of the long-COVID patients, the models were advanced enough to distinguish the severity of the compromised lung function, separating those with small airways disease from those with more advanced respiratory issues.

“The new element to the model is taking information from 3D CT scans showing lung volume and transferring that information to a model that will show these same characteristics in 2D images,” says Ching-Long Lin, Edward M. Mielnik and Samuel R. Harding professor and chair of the Department of Mechanical Engineering in the College of Engineering at Iowa. “Clinicians would be able to use chest X-rays to detect these outcomes. That’s the bigger perspective.”

The researchers based their modeling on CT scans of 100 people who were infected with the original COVID strain and went to UI Hospitals & Clinics for diagnosis for breathing problems between June and December 2020. Many of these long-COVID patients had small airways disease, a diagnosis reported by Alejandro Comellas, clinical professor of internal medicine–pulmonary, critical care, and occupational medicine, in a paper published last March in the journal Radiology.

Small airways disease affects a network of more than 10,000 tubes at the nexus in the lung where oxygenated air mixes with blood to be carried throughout the body. People with small airways disease have many of these vessels constricted, thus limiting the oxygen-blood exchange in the lungs, and impeding breathing overall.

Lin and his team collected data points at two intervals in the CT lung scans—when the patient inhaled and when the patient exhaled. The researchers compared their results with a control group that had not contracted the virus as they created the contrastive learning model.

“Our models successfully identified decreased lung function from long-COVID patients compared to those who had not gotten the virus,” says Lin, whose expertise is in machine learning and computational fluid and particle dynamic simulation.

Lin’s team advanced the model so it could separate patients with small airways disease from those with more advanced complications, such as emphysema.

“The study demonstrated in an independent way that patients with post-COVID have two types of lung injuries (small airway disease and lung parenchyma fibrosis/inflammation) that are persistent after having recovered from their initial SARS CoV-2 infection,” says Comellas, a co-author on this study.

“Chest X-rays are accessible, while CT scans are more expensive and not as accessible,” Lin adds. “Our model can be further improved, and I believe there is potential for it to be used at all clinics without having to buy expensive imaging equipment, such as CT scanners.”

The authors note the study is limited, in part because the sample size is small, and the patients are from a single medical facility. A larger sample size, they write, may uncover more variations in lung function stemming from long COVID.

The study, “Contrastive learning and subtyping of post-COVID-19 lung computed tomography images,” was published online Oct. 11 in the journal Frontiers in Physiology.

Co-authors, all from Iowa, include Frank Li, Xuan Zhang, Eric Hoffman, and Tianbao Yang.

The National Heart, Lung, and Blood Institute, a branch of the U.S. National Institutes of Health; and the U.S. Department of Education funded the research.

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JOURNAL

Frontiers in Physiology

DOI

10.3389/fphys.2022.999263 

METHOD OF RESEARCH

Computational simulation/modeling

SUBJECT OF RESEARCH

People

ARTICLE TITLE

Contrastive learning and subtyping of post-COVID-19 lung computed tomography images

New study reviews evidence of racism in emergency medicine, sets research agenda

Evidence-based interventions to address and eliminate racism and other systems of oppression in health care needed

Peer-Reviewed Publication

BOSTON UNIVERSITY SCHOOL OF MEDICINE

(Boston)—In 2021, the Society for Academic Emergency Medicine (SAEM) held a consensus conference, From Bedside to Policy: Advancing Social Emergency Medicine and Population Health, which included identifying priority areas for future research and implementation science related to race, racism and antiracism in emergency medicine (EM).

In an effort to identify and summarize existing research and set the agenda for EM research in these topic areas, researchers from institutions across the country, including Boston University Chobanian & Avedisian School of Medicine, conducted a literature review of articles that addressed how race and/or racism affect emergency medical care, including access, utilization, treatment, outcomes, patient experience or provider experience in the emergency department.

“Although more overt forms of racist rhetoric are less likely to be observed in the 21st century, many treatments and guidelines in use today were developed based on research that conceptualized race as biological rather than a social construct,” explained corresponding author Emily Cleveland Manchanda, MD, MPH, assistant professor of emergency medicine.

Among their findings:

• EM and adjacent fields have extensively documented racial inequities in access, utilization, diagnosis, treatment and outcomes over the course of many decades. Despite this, very few studies have explicitly studied racism or anti-racism in EM in any capacity.

 

• The majority of included studies were observational. Methods for reporting racial and ethnic inequities varied between studies, and many did not clearly report methods of collecting racial and ethnic data.

 

• Of the 187 studies included in the literature review, only six evaluated an intervention aimed at reducing racial inequities.

According to the researchers, key research priorities were informed by this review and refined through a robust consensus process that included input from community organizations around the country.  The research agenda presented in this article provides a roadmap for addressing and eliminating racism and other systems of oppression in emergency medicine.

 

“While the harmful consequences of racism in emergency medicine have been well documented in nearly every facet of our literature, the research agenda proposed in this study will help us move beyond identifying the problem and toward developing solutions that get at the root causes of racial health inequities. In particular, we identified an urgent need for researchers to focus on developing evidence-informed interventions to address and eliminate racism and other systems of oppression in health care,” added Cleveland Manchanda, who also is assistant program director of the Ravin Davidoff Executive Fellowship in Health Equity at Boston Medical Center and the Director for Social Justice Education and Implementation at the American Medical Association.

These findings appear online in the journal Academic Emergency Medicine.

 

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JOURNAL

Academic Emergency Medicine

DOI

10.1111/acem.14601 

METHOD OF RESEARCH

Literature review

SUBJECT OF RESEARCH

Not applicable

ARTICLE TITLE

Race, Racism and Antiracism in Emergency Medicine: A Scoping Review of the Literature and Research Agenda for the Future

Yeast fungus with the potential to become global health problem

Peer-Reviewed Publication

UNIVERSITY OF SOUTHERN DENMARK

The story of Candida auris starts in 2009, when a 70-year-old Japanese woman is a patient at the Tokyo Metropolitan Geriatric Hospital. Something discharges from one of her ears, and the doctors routinely take samples of it with a cotton swab. They analyze the sample to find out what is causing the infection.

It turns out that a yeast is at play, and it's different from other known yeasts. We are all familiar with baker’s yeast, a friendly microorganism, which is used to make beer and bred. Candida auris and other Candida yeast species are very different; they cause harmful and persistent infections, which are difficult to treat with known antibiotics.

Break out in a London hospital

Against all expectations, Candida auris turns out to be unusually stress-resistant. The discovery is so unusual that the doctors decide to describe it in a scientific journal; they name it Candida auris after the place where it was found – auris means ear in Latin. Since then, the yeast has spread to all continents. Patients are almost always weakened people, and cases are almost always recorded in hospitals.

In 2015, for example, an acute infection with Candida auris has run out of control at the Royal Brompton Hospital in London . For three months, the staff have tried everything to get rid of the infections, and finally they attempt a week-long spray attack. All surfaces in infected rooms are sprayed with hydrogen peroxide in the hope that the spray will reach all crevices and corners.

The spray device runs for a week, and to test if any microorganisms have survived, a gel-coated plate is then placed in the middle of the room. If any micro-organisms have survived the week-long spray attack, they will be attracted to the gel and thus reveal their existence. Only one organism appears on the gel plate. Candida auris.

The first case in Denmark

In 2022, a Danish person returns home from South Africa to be admitted to a Danish hospital. The person has several wounds that need to be treated, and the South African doctors have discovered Candida auris on the patients’ skin.

The presence of a fungus on the skin is not in itself dangerous - it becomes so only when it enters the bloodstream -, but the Danish hospital takes extra safety measures to ensure that Candida auris does not spread to other patients in the hospital: The patient is admitted to two rooms, so that there is also room for the equipment needed for examinations. This ensures that the patient does not have to be moved around to other departments.

To get to the two isolated rooms, staff has to go through two locks. The patient recovers and is discharged, and over a 24-hour period everything is disinfected in the rooms and in the locks.

Four cases in Denmark, so far

The next patient admitted to one of these two rooms stays there for only five hours – but that is enough for the patient to become infected with Candida auris in the bloodstream.

- It is difficult to understand how this could happen, said Maiken Cavling Arendrup, professor and head of the Unit for Mycology, Statens Serum Institut in Denmark, who has followed the cases.

To date, four cases of Candida auris have been registered in Denmark, all from 2022. The three cases are on the skin of people who have returned home from abroad, while the fourth – the patient who was infected after five hours in the hospital room – was infected in the blood. Both the three carriers and the infected patient have recovered.

Need for better treatment

 - The problem with this yeast is that it is very difficult to kill. It is multi-resistant, and thus you risk serious infections that cannot be treated, said Maria Szomek from Daniel Wüstner’s research group, Department of Biochemistry and Molecular Biology, adding:

- There are many types of medicine on the market that can fight fungal infections – including Candida auris.  But they are becoming less and less effective, because Candida auris is extremely good at developing resistance, so the challenge now is to develop better medicines that work. This means medicine, which not only inhibits growth of yeast but actually kills any remaining yeast cells.

Existing medicines against Candida auris and other yeasts with the potential to kill the cells are often based on so-called polyenes. Polyenes are a group of substances found naturally in certain bacteria as part of their inborn defense system. Polyenes can be extracted from the bacteria for medical use.

Can we improve nature’s own defense system?

But, as Maria Szomek points out; the mechanisms by which the polyenes kill yeast are not very well understood. This, however, is essential for developing new and improved polyene-based drugs.

- Therefore we are working on understanding how nature's own polyenes work, Maria Szomek said.

This work takes place in Daniel Wüstner's research group at the Department of Biochemistry and Molecular Biology. In their laboratory, the group uses advanced microscopy to study what happens to a yeast cell when attacked by polyenes. The group has teamed up with colleagues in theoretical and computational chemistry, Peter Reinholdt and Jacob Kongsted and is also working with two German research teams at Leipzig University and Humboldt University Berlin.

Precision attack in the cell

The researchers do not work with real Candida auris cells, but instead with harmless models, which they expose to polyenes from the fungicide Natamycin.

- We are interested in things like: how do the polyenes get through the cell membrane? How do they bind to and interact with ergosterol, which is a subgroup of steroids and the target of the polyenes' attack, Maria Szomek explained.

The group has described their latest study of this mechanism in a scientific article, which can be viewed here https://doi.org/10.1016/j.bbamem.2022.184012

 

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JOURNAL

Biochimica et Biophysica Acta (BBA) - Biomembranes

DOI

10.1016/j.bbamem.2022.184012 

METHOD OF RESEARCH

Imaging analysis

SUBJECT OF RESEARCH

People

ARTICLE TITLE

Natamycin sequesters ergosterol and interferes with substrate transport by the lysine transporter Lyp1 from yeast

ARTICLE PUBLICATION DATE

1-Nov-2022

Study: Schools’ social media posts may be compromising student privacy

US schools have shared an estimated 4.9 million Facebook posts with identifiable images of students

Peer-Reviewed Publication

AMERICAN EDUCATIONAL RESEARCH ASSOCIATION

Washington, November 2, 2022—U.S. schools and school districts have shared an estimated 4.9 million posts that include identifiable images of students on public Facebook pages, unintentionally putting student privacy at risk, according to a new study. Around 726,000 of these posts are thought to identify one or more students by their first and last names. The research was published today in Educational Researcher, a peer-reviewed journal of the American Educational Research Association.

The study examined publicly accessible posts on U.S. school and school district Facebook pages from 2005 to 2020. During that time, schools published about 18 million posts, with the annual frequency of posts, and the proportion of posts with photos, increasing each year. Public Facebook posts are accessible by all visitors to the platform, including those without a Facebook account.

Video: Coauthor Joshua M. Rosenberg discusses major findings and implications of the research

“While the percentage of Facebook posts that identified students was small, the sheer volume of posts meant that hundreds of thousands of students had personally identifiable information shared by their schools,” said coauthor Joshua M. Rosenberg, an assistant professor of STEM education at the University of Tennessee, Knoxville. “These findings suggest that student privacy may inadvertently be threatened by the social media activity of schools and districts.”

While previous research has looked at how social media sharing by individual educators may place the privacy of students at risk, Rosenberg notes this study is the first to consider the privacy implications of social media activities undertaken by schools and districts.  

Rosenberg conducted the study with Conrad Borchers (Carnegie Mellon University), Macy A. Burchfield (University of Tennessee, Knoxville), Daniel Anderson (Abl Schools), Sondra M. Stegenga (University of Utah), and Christian Fischer (University of Tübingen).

Using CrowdTangle, Facebook’s tool for scholars and journalists that provides access to data on the platform’s public posts, the researchers accessed public Facebook posts from all public schools and school districts in the United States. They found the posts by searching for links to Facebook pages from school and district website homepages. Thus, only schools and districts that linked to their Facebook page from their homepage were included in the sample.

The researchers found that of the 18 million posts, approximately 13.9 million included images of individuals of any age. Extrapolating from an analysis of a randomly selected sample of posts, the researchers estimated that 4.9 million of the posts had identifiable images of students, and 726,000 of these identified students’ first and last names.

“The posts we studied may represent the largest existing collection of publicly accessible, identifiable images of minors,” said Rosenberg. “It is likely that the photos are being accessed by a range of actors, including government agencies, predictive policing companies, and those with nefarious intent.”

The study notes that government agencies in the U.S. and other countries regularly access public social media data for purposes ranging from monitoring immigration and predicting crime risks to documenting social connections. It also notes that the Australian government’s online safety agency has reported that tens of millions of harmless images of minors originally shared on social media have been downloaded and saved on child exploitation sites.

“The threat to privacy will continue to grow, perhaps quickly, due to expanding facial recognition technology,” said Rosenberg. He also explained that a simple reverse image search on Google could link a student to other sources of personally identifiable information online.

Rosenberg and his coauthors said there are practical steps that school leaders could take to mitigate risks. These include not including students’ full names in posts; asking parents to opt in to, rather than opt out of, the sharing of their children’s information on school social media; making it easy for parents to request that photos of their children be removed; and making school or district pages private.

Media companies, Rosenberg added, should consider changing the default settings for schools, automatically making pages private, which would drastically reduce the risk that student information is collected at a large scale for unintended secondary uses.

He also noted policymakers and government regulators could do more to reduce the risk that schools and other organizations that serve children will inadvertently compromise children’s privacy.

“As a nation, the U.S. needs to devote greater attention and resources to mitigating the potential downsides of the pervasive sharing of children’s information on social media, particularly when it is organizations such as schools and districts that are doing the sharing,” said Rosenberg.

The study’s authors acknowledged the importance of parent engagement efforts, including the use of social media by schools. However, they noted this must always be balanced with safety and privacy protections on multiple levels.

“While parents and schools can take steps to protect student privacy, it is also the responsibility of social media platforms and the wider society to ensure that policies and regulations keep pace with rapidly evolving technology, Rosenberg said.

Study Citation: Rosenberg, J. M., Borchers, C., Burchfield, M. A., Anderson, D., Stegenga, S. M., & Fischer, C. (2022). Posts about students on Facebook: A data ethics perspective. Educational Researcher. Prepublished November 2, 2022. https://www.doi.org/10.3102/0013189X221120538.

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About AERA
The American Educational Research Association (AERA) is the largest national interdisciplinary research association devoted to the scientific study of education and learning. Founded in 1916, AERA advances knowledge about education, encourages scholarly inquiry related to education, and promotes the use of research to improve education and serve the public good. Find AERA on Facebook, Twitter, and Instagram.

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JOURNAL

Educational Researcher

DOI

10.3102/0013189X221120538 

ARTICLE TITLE

Posts About Students on Facebook: A Data Ethics Perspective