These findings hint at the role of pre-existing conditions in raising the risk of an individual having a severe case of COVID-19 once infected
At the University of Michigan, a team of pathologists have been researching the factors that might cause some patients infected by SARS-CoV-2 to suffer persistent respiratory problems, often described as “long COVID.” They have identified factors that place some individuals at higher risk for these problems.
Little is known about how the SARS-CoV-2 coronavirus affects the body long-term. Millions of people who have survived COVID-19 infections are living with chronic symptoms, including persistent respiratory problems such as shortness of breath. However, until now, it was not clear what may be causing these symptoms in some people but not others, even after the coronavirus has completely cleared their bodies.
Now, anatomic pathologists at Michigan Medicine, formerly the University of Michigan Health, believe they may have discovered what is causing ongoing respiratory problems in some patients who have recovered from the COVID-19 infection—pre-existing conditions.
The researchers examined lung biopsies from COVID-19 patients who continued to experience lingering symptoms. They discovered in some individuals lung damage that was present prior to contracting the virus.
“Some of the early publications and popular press around long COVID has implied or assumed that once you had COVID, everything that happens next is COVID-related,” said anatomic pathologist and senior author of the study Jeffrey Myers, MD (above), Vice Chair for Clinical Affairs and Quality at Michigan Medicine, in a news release. “Of course, that might or might not be true,” he added. (Photo copyright: University of Michigan.)
The research team analyzed lung biopsies from 18 COVID-19 survivors who were still experiencing respiratory symptoms or had abnormal computed tomography (CT) scans after the virus was no longer present in their bodies. The researchers found ground glass opacities on the radiological scans of 14 of those patients.
According to the news release, this finding indicates there were “areas of the lungs that appear as a cloudy gray color as opposed to the dark color of normal air-filled lungs, on a chest X-ray or CT scan.”
The biopsies exhibited evidence of pre-existing lung scarring and proof of diffuse alveolar damage, which is typically seen in patients with acute respiratory illnesses. Only five of the patients examined in the study were known to have lung disease prior to their COVID-19 diagnoses.
The researchers found that the most common condition present in these 18 patients was usual interstitial pneumonia (UIP). This condition, also known clinically as idiopathic pulmonary fibrosis (IPF), is a common form of pulmonary fibrosis that is characterized by progressive scarring and stiffening of both lungs.
“We were seeing a lot of UIP, which isn’t the pattern we tend to associate with acute lung injury,” said Kristine Konopka, MD, Clinical Associate Professor at Michigan Medicine and lead author of the study, in the news release. “So, we think these are patients who had lung disease prior to COVID and maybe they just weren’t being followed by primary care physicians. They then had COVID, are still sick, and their UIP is finally being picked up.”
Could Patients Have Lung Disease and Not Know it?
“The notion,” Myers noted in the news release, “that a person could have chronic lung damage and not know it was unheard of until relatively recently.” He also explained that UIP/IPF is a progressive disease that gets worse with time and that an infection like COVID-19 can accelerate the illness to a more serious condition known as an acute exacerbation of IPF, which can lead to death.
“SARS-CoV-2 comes along and does to the lung, from a pathology perspective, exactly what happens with an acute exacerbation,” Myers said.
The researchers also stated that it’s impossible to determine for certain whether the SARS-CoV-2 virus caused the UIP/IPF without the existence of full clinical histories of the patients prior to their COVID-19 diagnoses. They hope their research will motivate clinicians to be cautious before automatically attributing respiratory symptoms to long COVID in survivors of the virus. It is possible that the lung damage was present prior to the coronavirus.
“You shouldn’t make assumptions but [instead] ask the right questions, the first of which would be ‘I wonder if this is really COVID?’ What you do after that depends on the answer to that question,” he added.
This research is an example of how pathologists can add insight and value into the deeper understanding of the processes involved in specific diseases. Dark Daily invites any of our readers who are aware of other pathologist-authored studies or published papers about COVID-19 to alert us to the availability of those works.
International research team that developed swarm learning believe it could ‘significantly promote and accelerate collaboration and information exchange in research, especially in the field of medicine’
“Swarm Learning” is a technology that enables cross-site analysis of population health data while maintaining patient privacy protocols to generate improvements in precision medicine. That’s the goal described by an international team of scientists who used this approach to develop artificial intelligence (AI) algorithms that seek out and identify lung disease, blood cancer, and COVID-19 data stored in disparate databases.
Since 80% of patient records feature clinical laboratory test results, there’s no doubt this protected health information (PHI) would be curated by the swarm learning algorithms.
In their study they wrote, “Fast and reliable detection of patients with severe and heterogeneous illnesses is a major goal of precision medicine. … However, there is an increasing divide between what is technically possible and what is allowed, because of privacy legislation. Here, to facilitate the integration of any medical data from any data owner worldwide without violating privacy laws, we introduce Swarm Learning—a decentralized machine-learning approach that unites edge computing, blockchain-based peer-to-peer networking, and coordination while maintaining confidentiality without the need for a central coordinator, thereby going beyond federated learning.”
What is Swarm Learning?
Swarm Learning is a way to collaborate and share medical research toward a goal of advancing precision medicine, the researchers stated.
The technology blends AI with blockchain-based peer-to-peer networking to create information exchange across a network, the DZNE news release explained. The machine learning algorithms are “trained” to detect data patterns “and recognize the learned patterns in other data as well,” the news release noted.
“Medical research data are a treasure. They can play a decisive role in developing personalized therapies that are tailored to each individual more precisely than conventional treatments,” said Joachim Schultze, MD (above), Director, Systems Medicine at DZNE and Professor, Life and Medical Sciences Institute at the University of Bonn, in the news release. “It’s critical for science to be able to use such data as comprehensively and from as many sources as possible,” he added. This, of course, would include clinical laboratory test results data. (Photo copyright: University of Bonn.)
Since, as Dark Daily has reported many times, clinical laboratory test data comprises as much as 80% of patients’ medical records, such a treasure trove of information will most likely include medical laboratory test data as well as reports on patient diagnoses, demographics, and medical history. Swarm learning incorporating laboratory test results may inform medical researchers in their population health analyses.
“The key is that all participants can learn from each other without the need of sharing confidential information,” said Eng Lim Goh, PhD, Senior Vice President and Chief Technology Officer for AI at Hewlett Packard Enterprise (HPE), which developed base technology for swarm learning, according to the news release.
An HPE blog post notes that “Using swarm learning, the hospital can combine its data with that of hospitals serving different demographics in other regions and then use a private blockchain to learn from a global average, or parameter, of results—without sharing actual patient information.
“Under this model,” the blog continues, “‘each hospital is able to predict, with accuracy and with reduced bias, as though [it has] collected all the patient data globally in one place and learned from it,’ Goh says.”
Swarm Learning Applied in Study
The researchers studied four infectious and non-infectious diseases:
They used 16,400 transcriptomes from 127 clinical studies and assessed 95,000 X-ray images.
Data for transcriptomes were distributed over three to 32 blockchain nodes and across three nodes for X-rays.
The researchers “fed their algorithms with subsets of the respective data set” (such as those coming from people with disease versus healthy individuals), the news release noted.
Findings included:
90% algorithm accuracy in reporting on healthy people versus those diagnosed with diseases for transcriptomes.
76% to 86% algorithm accuracy in reporting of X-ray data.
Methodology worked best for leukemia.
Accuracy also was “very high” for tuberculosis and COVID-19.
X-ray data accuracy rate was lower, researchers said, due to less available data or image quality.
“Our study thus proves that swarm learning can be successfully applied to very different data. In principle, this applies to any type of information for which pattern recognition by means of artificial intelligence is useful. Be it genome data, X-ray images, data from brain imaging, or other complex data,” Schultze said in the DZNE news release.
The scientists say hospitals as well as research institutions may join or form swarms. So, hospital-based medical laboratory leaders and pathology groups may have an opportunity to contribute to swarm learning. According to Schultze, sharing information can go a long way toward “making the wealth of experience in medicine more accessible worldwide.”
Genomic sequencing continues to benefit patients through precision medicine clinical laboratory treatments and pharmacogenomic therapies
EDITOR’S UPDATE—Jan. 26, 2022: Since publication of this news briefing, officials from Genomics England contacted us to explain the following:
The “five million genome sequences” was an aspirational goal mentioned by then Secretary of State for Health and Social Care Matt Hancock, MP, in an October 2, 2018, press release issued by Genomics England.
As of this date a spokesman for Genomics England confirmed to Dark Daily that, with the initial goal of 100,000 genomes now attained, the immediate goal is to sequence 500,000 genomes.
This goal was confirmed in a tweet posted by Chris Wigley, CEO at Genomics England.
In accordance with this updated input, we have revised the original headline and information in this news briefing that follows.
What better proof of progress in whole human genome screening than the announcement that the United Kingdom’s 100,000 Genome Project has not only achieved that milestone, but will now increase the goal to 500,000 whole human genomes? This should be welcome news to clinical laboratory managers, as it means their labs will be positioned as the first-line provider of genetic data in support of clinical care.
Many clinical pathologists here in the United States are aware of the 100,000 Genome Project, established by the National Health Service (NHS) in England (UK) in 2012. Genomics England’s new goal to sequence 500,000 whole human genomes is to pioneer a “lasting legacy for patients by introducing genomic sequencing into the wider healthcare system,” according to Technology Networks.
The importance of personalized medicine and of the power of precise, accurate diagnoses cannot be understated. This announcement by Genomics England will be of interest to diagnosticians worldwide, especially doctors who diagnose and treat patients with chronic and life-threatening diseases.
Building a Vast Genomics Infrastructure
Genetic sequencing launched the era of precision medicine in healthcare. Through genomics, drug therapies and personalized treatments were developed that improved outcomes for all patients, especially those suffering with cancer and other chronic diseases. And so far, the role of genomics in healthcare has only been expanding, as Dark Daily covered in numerous ebriefings.
Genomics England, which is wholly owned by the Department of Health and Social Care in the United Kingdom, was formed in 2012 with the goal of sequencing 100,000 whole genomes of patients enrolled in the UK National Health Service. That goal was met in 2018, and now the NHS aspires to sequence 500,000 genomes.
“The last 10 years have been really exciting, as we have seen genetic data transition from being something that is useful in a small number of contexts with highly targeted tests, towards being a central part of mainstream healthcare settings,” Richard Scott, MD, PhD (above), Chief Medical Officer at Genomics England told Technology Networks. Much of the progress has found its way into clinical laboratory testing and precision medicine diagnostics. (Photo copyright: Genomics England.)
Genomics England’s initial goals included:
To create an ethical program based on consent,
To set up a genomic medicine service within the NHS to benefit patients,
To make new discoveries and gain insights into the use of genomics, and
To begin the development of a UK genomics industry.
To gain the greatest benefit from whole genome sequencing (WGS), a substantial amount of data infrastructure must exist. “The amount of data generated by WGS is quite large and you really need a system that can process the data well to achieve that vision,” said Richard Scott, MD, PhD, Chief Medical Officer at Genomics England.
In early 2020, Weka, developer of the WekaFS, a fully parallel and distributed file system, announced that it would be working with Genomics England on managing the enormous amount of genomic data. When Genomics England reached 100,000 sequenced genomes, it had already gathered 21 petabytes of data. The organization expects to have 140 petabytes by 2023, notes a Weka case study.
Putting Genomics England’s WGS Project into Action
WGS has significantly impacted the diagnosis of rare diseases. For example, Genomics England has contributed to projects that look at tuberculosis genomes to understand why the disease is sometimes resistant to certain medications. Genomic sequencing also played an enormous role in fighting the COVID-19 pandemic.
Scott notes that COVID-19 provides an example of how sequencing can be used to deliver care. “We can see genomic influences on the risk of needing critical care in COVID-19 patients and in how their immune system is behaving. Looking at this data alongside other omics information, such as the expression of different protein levels, helps us to understand the disease process better,” he said.
What’s Next for Genomics Sequencing?
As the research continues and scientists begin to better understand the information revealed by sequencing, other areas of scientific study like proteomics and metabolomics are becoming more important.
“There is real potential for using multiple strands of data alongside each other, both for discovery—helping us to understand new things about diseases and how [they] affect the body—but also in terms of live healthcare,” Scott said.
Along with expanding the target of Genomics England to 500,000 genomes sequenced, the UK has published a National Genomic Strategy named Genome UK. This plan describes how the research into genomics will be used to benefit patients. “Our vision is to create the most advanced genomic healthcare ecosystem in the world, where government, the NHS, research and technology communities work together to embed the latest advances in patient care,” according to the Genome UK website.
Clinical laboratories professionals with an understanding of diagnostics will recognize WGS’ impact on the healthcare industry. By following genomic sequencing initiatives, such as those coming from Genomics England, pathologists can keep their labs ready to take advantage of new discoveries and insights that will improve outcomes for patients.
One key finding of interest to clinical laboratory scientists is that this research study indicates that the human microbiome may more closely correlate with blood markers of metabolic disease than the genome of individuals
In the search for more sensitive diagnostic biomarkers (meaning the ability to detect disease with smaller samples and smaller quantities of the target biomarker), an international team of researchers has teased out a finding that a panel of multiple biomarkers in the human microbiome is more closely correlated with metabolic disease than genetic markers.
The team also discovered that the foods an individual ate had a more powerful impact on their microbiomes than their genes. The study participants included several sets of identical twins. The researchers found that identical twins shared only about 34% of the same gut microbes. People who were unrelated shared 30% of the same gut microbes.
This is a fascinating insight for pathologists and microbiologists involved in the study of the human microbiome for use in development of precision medicine clinical laboratory testing and drug therapies.
Microbiome Markers for Obesity, Heart Disease, and More
The study began in 2018, when an international team of researchers analyzed the gut microbiomes, diets, and blood biomarkers for cardiometabolic health obtained from 1,100 mostly healthy adults in the United Kingdom (UK) and the United States (US). They collected blood samples from the participants before and after meals to examine blood sugar levels, hormones, cholesterol, and inflammation levels. Sleep and activity levels also were monitored. Participants had to wear a continuous glucose monitor for two weeks during the research period.
The scientists discovered that the composition of a healthy gut microbiome is strongly linked to certain foods, food groups, nutrients, and diet composition. They identified markers for obesity, impaired glucose tolerance, and cardiovascular disease in the gut bacteria.
“When you eat, you’re not just nourishing your body, you’re feeding the trillions of microbes that live inside your gut,” genetic epidemiologist Tim Spector, MD, FmedSCi, told Labroots. Spector is a professor of genetic epidemiology at King’s College London and one of the authors of the study.
The scientists found that a diet rich in nutrient-dense, whole foods was more beneficial to a healthy gut microbiome, which can be an indicator of good health. Individuals who ate minimally processed foods, such as vegetables, nuts, eggs, and seafood were more likely to have healthy gut bacteria than individuals who consumed large amounts of highly processed foods, like juices and other sweetened beverages, processed meats, and refined grains and foods that were high in added sugars and salt.
“It goes back to the age-old message of eating as many whole and unprocessed foods as possible,” Sarah Berry, PhD, a nutrition scientist at King’s College London and a co-author of the study told The New York Times. “What this research shows for the first time is the link between the quality of the food we’re eating, the quality of our microbiomes, and ultimately our health outcomes,” she added.
The researchers concluded that heavily processed foods tend to contain very minimal amounts of fiber, a macronutrient that helps promote good bacteria in the gut microbiome and leads to better metabolic and cardiovascular health.
They found that people who had healthy blood sugar levels following a meal had higher levels of good bacteria called Prevotella copri, a genus of gram-negative bacteria, and Blastocystis, a genus of single-celled heterokont parasites, present in their guts. These bacteria are associated with lower levels of visceral fat, which accumulates around internal organs and increases risk of heart disease.
These “good” microbes also are affiliated with lower levels of inflammation, better blood sugar control, and lower spikes in blood fat and cholesterol levels after meals.
“We were surprised to see such large, clear groups of what we informally call ‘good’ and ‘bad’ microbes emerging from our analysis,” Nicola Segata, PhD (above), told News Medical. Segata is a professor and principal investigator at the Computational Metagenomics Lab at the University of Trento in Italy, and co-author of the study. “It is also exciting to see that microbiologists know so little about many of these microbes that they are not even named yet. This is now a big area of focus for us, as we believe they may open new insights in the future into how we could use the gut microbiome as a modifiable target to improve human metabolism and health,” he added. Pathologists and clinical laboratory scientists who read Dark Daily are already familiar with the plethora of ways the human microbiome is being studied for use in diagnostic testing and drug therapy. (Photo copyright: University of Trento.)
The study also found that different people have wildly varying metabolic responses to the same foods, partially due to the types of bacteria residing in their gut microbiome. The consumption of some foods is better for overall health than other foods, but there is no definitive, one-size-fits-all diet that works for everyone.
“What we found in our study was that the same diet in two different individuals does not lead to the same microbiome, and it does not lead to the same metabolic response. There is a lot of variation,” Andrew Chan, MD, Professor of Medicine at Harvard Medical School, told The New York Times. Chan is also Chief of the Clinical and Translational Epidemiology Unit at Massachusetts General Hospital and co-author of the study.
Small Changes in Diet, Big Impact to Health
The team is now planning a clinical trial to test whether changes in diet can alter levels of good and bad microbes in the gut. If proven to be true, such information could help clinicians design personalized nutritional plans that would enable individuals to improve their gut microbiome and their overall health.
“As a nutritional scientist, finding novel microbes that are linked to specific foods, as well as metabolic health, is exciting,” Berry told News Medical. “Given the highly personalized composition of each individual’s microbiome, our research suggests that we may be able to modify our gut microbiome to optimize our health by choosing the best foods for our unique biology.
“We think there are lots of small changes that people can make that can have a big impact on their health that might be mediated through the microbiome,” Berry told The New York Times.
More research and clinical trials are needed before diagnostic tests that use microbiome biomarkers to detect metabolic diseases can be developed. But these early research findings are a sign to pathologists and clinical laboratory managers that microbiome-based assays may come to play a more significant role in the early detection of several metabolic diseases.
Though the new technology could speed diagnoses of cancers and other skin diseases, it would also greatly reduce dermatopathology biopsy referrals and revenue
What effect would elimination of tissue biopsies have on dermatopathology and clinical laboratory revenue? Quite a lot. Dermatologists alone account for a significant portion of skin biopsies sent to dermatopathologists. Thus, any new technology that can “eliminate the need for invasive skin biopsies” would greatly reduce the number of histopathological referrals and reduce revenue to those practices.
“What if we could entirely bypass the biopsy process and perform histology-quality staining without taking tissue and processing tissue in a noninvasive way? Can we create images that diagnosticians can benefit from?” asked Aydogan Ozcan, PhD (above), Chancellor’s Professor of Electrical and Computer Engineering at UCLA’s Samueli School of Engineering, one of the scientists who developed UCLA’s new virtual histology method, during an interview with Medical Device + Diagnostic Industry (MD+DI). (Photo copyright: Nature.)
Could Skin Biopsies be Eliminated?
The UCLA researchers believe their innovative deep learning-enabled imaging framework could possibly circumvent the need for skin biopsies to diagnose skin conditions.
“Here, we present a deep learning-based framework that uses a convolutional neural network to rapidly transform in vivo RCM images of unstained skin into virtually-stained hematoxylin and eosin-like images with microscopic resolution, enabling visualization of the epidermis, dermal-epidermal junction, and superficial dermis layers.
“This application of deep learning-based virtual staining to noninvasive imaging technologies may permit more rapid diagnoses of malignant skin neoplasms and reduce invasive skin biopsies,” the researchers added in their published study.
According to the published study, the UCLA team trained their neural network under an adversarial machine learning scheme to transform grayscale RCM images into virtually stained 3D microscopic images of normal skin, basal cell carcinoma, and pigmented melanocytic nevi. The new images displayed similar morphological features to those shown with the widely used hematoxylin and eosin (H&E) staining method.
“In our studies, the virtually stained images showed similar color contrast and spatial features found in traditionally stained microscopic images of biopsied tissue,” Ozcan told Photonics Media. “This approach may allow diagnosticians to see the overall histological features of intact skin without invasive skin biopsies or the time-consuming work of chemical processing and labeling of tissue.”
The framework covers different skin layers, including the epidermis, dermal-epidermis, and superficial dermis layers. It images deeper into tissue without being invasive and can be quickly performed.
“The virtual stain technology can be streamlined to be almost semi real time,” Ozcan told Medical Device + Diagnostic Industry (MD+DI). “You can have the virtual staining ready when the patient is wrapping up. Basically, it can be within a couple of minutes after you’re done with the entire imaging.”
Currently, medical professionals rely on invasive skin biopsies and histopathological evaluations to diagnose skin diseases and cancers. These diagnostic techniques can result in unnecessary biopsies, scarring, multiple patient visits and increased medical costs for patients, insurers, and the healthcare system.
Improving Time to Diagnosis through Digital Pathology
Another advantage of this virtual technology, the UCLA researchers claim, is that it can provide better images than traditional staining methods, which could improve the ability to diagnose pathological skin conditions and help alleviate human error.
“The majority of the time, small laboratories have a lot of problems with consistency because they don’t use the best equipment to cut, process, and stain tissue,” dermatopathologist Philip Scumpia, MD, PhD, Assistant Professor of Dermatology and Dermatopathology at UCLA Health and one of the authors of the research paper, told MD+DI.
“What ends up happening is we get tissue on a histology slide that’s basically unevenly stained, unevenly put on the microscope, and it gets distorted,” he added, noting that this makes it very hard to make a diagnosis.
Scumpia also added that this new technology would allow digital images to be sent directly to the pathologist, which could reduce processing and laboratory times.
“With electronic medical records now and the ability to do digital photography and digital mole mapping, where you can obtain a whole-body imaging of patients, you could imagine you can also use one of these reflectance confocal devices. And you can take that image from there, add it to the EMR with the virtual histology stain, which will make the images more useful,” Scumpia said. “So now, you can track lesions as they develop.
“What’s really exciting too, is that there’s the potential to combine it with other artificial intelligence, other machine learning techniques that can give more information,” Scumpia added. “Using the reflectance confocal microscope, a clinician who might not be as familiar in dermatopathology could take images and send [them] to a practitioner who could give a more expert diagnosis.”
Faster Diagnoses but Reduced Revenue for Dermatopathologists, Clinical Labs
Ozcan noted that there’s still a lot of work to be done in the clinical assessment, validation, and blind testing of their AI-based staining method. But he hopes the technology can be propelled into a useful tool for clinicians.
“I think this is a proof-of-concept work, and we’re very excited to make it move forward with further advances in technology, in the ways that we acquire 3D information [and] train our neural networks for better and faster virtual staining output,” he told MD+DI.
Though this new technology may reduce the need for invasive biopsies and expedite the diagnosis of skin conditions and cancers—thus improving patient outcomes—what affect might it have on dermatopathology practices?
More research and clinical studies are needed before this new technology becomes part of the diagnosis and treatment processes for skin conditions. Nevertheless, should virtual histology become popular and viable, it could greatly impact the amount of skin biopsy referrals to pathologists, dermatopathologists, and clinical laboratories, thus diminishing a great portion of their revenue.
Japanese scientists who developed the detection method hope to use it to create ‘easy testing kits that anyone can use’
What do ostriches and humans have in common during the current COVID-19 pandemic? The unexpected answer is that ostrich antibodies can be used to identify humans infected with COVID-19. If proven viable in healthcare settings, the possibility exists that new clinical laboratory tests could be developed based on wearable diagnostics technologies that pathologists would interpret for doctors and patients.
According to Study Finds, scientists at Kyoto Prefectural University in Japan have created a removable mask filter that, when sprayed with a fluorescent dye coated with antibodies extracted from ostrich eggs, will glow under UV light when COVID-19 is detected. The discovery by Yasuhiro Tsukamoto, PhD (above), President of Kyoto Prefectural University, and his researchers could lead to development of low-cost at home COVID-19 testing kits using the same ostrich-antibody-based technique. (Photo copyright: Kyoto Prefectural University/Reuters.)
The KPU scientists conducted a small study with 32 COVID-19 patients over a 10-day span. The surgical-style masks they wore later glowed around the nose and mouth areas but became dimmer over time as their viral load decreased.
“The ostrich antibody for corona placed on the mouth filter of the mask captures the coronavirus in coughing, sneezing, and water,” the researchers explained in Study Finds.
Tsukamoto himself learned he had contracted COVID-19 after wearing a prototype mask and noticing it glowed under UV light. A PCR test later confirmed his diagnosis, Kyodo News reported.
The KPU team “hopes to further develop the masks so they will glow automatically, without special lighting, if the [COVID-19] virus is detected.” Reuters noted in its coverage of the ostrich-antibody masks.
Making Medicine from Ostrich Antibodies
A profile in Audubon noted that Tsukamoto, who also serves as a veterinary medicine professor at Kyoto Prefectural University, made ostriches the focus of his research since the 1990s as he looked for ways to harness the dinosaur-like bird’s properties to fight human infections. He maintains a flock of 500 captive ostriches. Each female ostrich can produce 50 to 100 eggs/year over a 50-year life span.
Tsukamoto’s research focuses on customizing the antibodies in ostrich eggs by injecting females with inactive viruses, allergens, and bacteria, and then extracting the antibodies to develop medicines for humans. Antibodies form in the egg yolks in about six weeks and can be collected without harming the parent or young.
“The idea of using ostrich antibodies for therapeutics in general is a very interesting concept, particularly because of the advantages of producing the antibodies from eggs,” Ashley St. John, PhD, an Associate Professor in Immunology, at Duke-NUS Medical School in Singapore, told Audubon.
While more clinical studies will be needed before ostrich-antibody masks reach the commercial marketplace, Tsukamoto’s team is planning to expand their experiment to 150 participants with a goal of receiving Japanese government approval to begin selling the glowing COVID-detection masks as early as 2022. But they believe the ostrich-antibody technique ultimately may lead to development of an inexpensive COVID-19 testing kit.
“We can mass-produce antibodies from ostriches at a low cost. In the future, I want to make this into an easy testing kit that anyone can use,” Tsukamoto told Kyodo News.
Harvard, MIT Also Working on COVID-19 Detecting Facemask
According to Fast Company, the MIT/Harvard COVID-19-detecting masks use the same core technology as previous paper tests for Ebola and Zika that utilize proteins and nucleic acids embedded in paper that react to target molecules.
Fast Company explained that the mask wearer launches a test by pushing a button to release a small water reservoir embedded in the mask (above). Droplets from their breath are than analyzed by the sensors in the masks, which could be adapted to test for new COVID variants or other respiratory pathogens. In addition to eliminating the use of a nasal swab, the mask-based testing system may compete with clinical laboratory-based results. (Photo copyright: Felice Frankel/MIT.)
“They would especially be useful in situations where local variant outbreaks are occurring, allowing people to conveniently test themselves at home multiple times a day,” he told Fast Company.
“It’s on par specificity and sensitivity that you will get in a state-of-the-art [medical] laboratory, but with no one there,” Luis Ruben Soenksen, PhD, Venture Builder in Artificial Intelligence and Healthcare at MIT and one of the co-authors of the Nature Biotechnology study, told Fast Company.
As the definition of “wearable diagnostic technology” broadens, pathologists and clinical laboratory scientists may see their roles expand to include helping consumers interpret data collected by point-of-care testing technology as well as performing, evaluating, and interpreting laboratory test results that come from non-traditional sources.
