The ASBMB story notes that nanopore technology depends on differences in charges on either side of the membrane to force DNA or RNA through the hole. This is one reason why proteins pose such a challenge.
“Think of a cell as a miniature city, with proteins as its inhabitants. Each protein-resident has a unique identity, its own characteristics, and function. If there was a database cataloging the fingerprints, job profiles, and talents of the city’s inhabitants, such a database would undoubtedly be invaluable!” said Behzad Mehrafrooz, PhD (above), Graduate Research Assistant at University of Illinois at Urbana-Champaign in an article he penned for the university website. This research should be of interest to the many clinical laboratories that do protein testing. (Photo copyright: University of Illinois.)
How the Maglia Process Works
In a Groningen University news story, Maglia said protein is “like cooked spaghetti. These long strands want to be disorganized. They do not want to be pushed through this tiny hole.”
His technique, developed in collaboration with researchers at the University of Rome Tor Vergata, uses electrically charged ions to drag the protein through the hole.
“We didn’t know whether the flow would be strong enough,” Maglia stated in the news story. “Furthermore, these ions want to move both ways, but by attaching a lot of charge on the nanopore itself, we were able to make it directional.”
The researchers tested the technology on what Maglia described as a “difficult protein” with many negative charges that would tend to make it resistant to flow.
“Previously, only easy-to-thread proteins were analyzed,” he said in the news story. “But we gave ourselves one of the most difficult proteins as a test. And it worked!”
Maglia now says that he intends to commercialize the technology through a new startup called Portal Biotech.
Detecting Post-Translational Modifications in the UK
In another recent study, researchers at the University of Oxford reported that they have adapted nanopore technology to detect post-translational modifications (PTMs) in protein chains. The term refers to changes made to proteins after they have been transcribed from DNA, explained an Oxford news story.
“The ability to pinpoint and identify post-translational modifications and other protein variations at the single-molecule level holds immense promise for advancing our understanding of cellular functions and molecular interactions,” said contributing author Hagan Bayley, PhD, Professor of Chemical Biology at University of Oxford, in the news story. “It may also open new avenues for personalized medicine, diagnostics, and therapeutic interventions.”
Bayley is the founder of Oxford Nanopore Technologies, a genetic sequencing company in the UK that develops and markets nanopore sequencing products.
The news story notes that the new technique could be integrated into existing nanopore sequencing devices. “This could facilitate point-of-care diagnostics, enabling the personalized detection of specific protein variants associated with diseases including cancer and neurodegenerative disorders,” the story states.
In another recent study, researchers at the University of Washington reported that they have developed their own method for protein sequencing with nanopore technology.
“This opens up the possibility for barcode sequencing at the protein level for highly multiplexed assays, PTM monitoring, and protein identification!” Motone wrote.
Single-cell proteomics, enabled by nanopore protein sequencing technology, “could provide higher sensitivity and wider throughput, digital quantification, and novel data modalities compared to the current gold standard of protein MS [mass spectrometry],” they wrote. “The accessibility of these tools to a broader range of researchers and clinicians is also expected to increase with simpler instrumentation, less expertise needed, and lower costs.”
There are approximately 20,000 human genes. However, there are many more proteins. Thus, there is strong interest in understanding the human proteome and the role it plays in health and disease.
Technology that makes protein testing faster, more accurate, and less costly—especially with a handheld analyzer—would be a boon to the study of proteomics. And it would give clinical laboratories new diagnostic tools and bring some of that testing to point-of-care settings like doctor’s offices.
Researchers intend their new AI image retrieval tool to help pathologists locate similar case images to reference for diagnostics, research, and education
Researchers at Stanford University turned to an unusual source—the X social media platform (formerly known as Twitter)—to train an artificial intelligence (AI) system that can look at clinical laboratory pathology images and then retrieve similar images from a database. This is an indication that pathologists are increasingly collecting and storing images of representative cases in their social media accounts. They then consult those libraries when working on new cases that have unusual or unfamiliar features.
The Stanford Medicine scientists trained their AI system—known as Pathology Language and Image Pretraining (PLIP)—on the OpenPath pathology dataset, which contains more than 200,000 images paired with natural language descriptions. The researchers collected most of the data by retrieving tweets in which pathologists posted images accompanied by comments.
“It might be surprising to some folks that there is actually a lot of high-quality medical knowledge that is shared on Twitter,” said researcher James Zou, PhD, Assistant Professor of Biomedical Data Science and senior author of the study, in a Stanford Medicine SCOPE blog post, which added that “the social media platform has become a popular forum for pathologists to share interesting images—so much so that the community has widely adopted a set of 32 hashtags to identify subspecialties.”
“It’s a very active community, which is why we were able to curate hundreds of thousands of these high-quality pathology discussions from Twitter,” Zou said.
“The main application is to help human pathologists look for similar cases to reference,” James Zou, PhD (above), Assistant Professor of Biomedical Data Science, senior author of the study, and his colleagues wrote in Nature Medicine. “Our approach demonstrates that publicly shared medical information is a tremendous resource that can be harnessed to develop medical artificial intelligence for enhancing diagnosis, knowledge sharing, and education.” Leveraging pathologists’ use of social media to store case images for future reference has worked out well for the Stanford Medicine study. (Photo copyright: Stanford University.)
Retrieving Pathology Images from Tweets
“The lack of annotated publicly-available medical images is a major barrier for innovations,” the researchers wrote in Nature Medicine. “At the same time, many de-identified images and much knowledge are shared by clinicians on public forums such as medical Twitter.”
In this case, the goal “is to train a model that can understand both the visual image and the text description,” Zou said in the SCOPE blog post.
“Pathology is perhaps even more suited to Twitter than many other medical fields because for most pathologists, the bulk of our daily work revolves around the interpretation of images for the diagnosis of human disease,” wrote Jerad M. Gardner, MD, a dermatopathologist and section head of bone/soft tissue pathology at Geisinger Medical Center in Danville, Pa., in a blog post about the Pathology Hashtag Ontology project. “Twitter allows us to easily share images of amazing cases with one another, and we can also discuss new controversies, share links to the most cutting edge literature, and interact with and promote the cause of our pathology professional organizations.”
The researchers used the 32 subspecialty hashtags to retrieve English-language tweets posted from 2006 to 2022. Images in the tweets were “typically high-resolution views of cells or tissues stained with dye,” according to the SCOPE blog post.
The researchers collected a total of 232,067 tweets and 243,375 image-text pairs across the 32 subspecialties, they reported. They augmented this with 88,250 replies that received the highest number of likes and had at least one keyword from the ICD-11 codebook. The SCOPE blog post noted that the rankings by “likes” enabled the researchers to screen for high-quality replies.
They then refined the dataset by removing duplicates, retweets, non-pathology images, and tweets marked by Twitter as being “sensitive.” They also removed tweets containing question marks, as this was an indicator that the practitioner was asking a question about an image rather than providing a description, the researchers wrote in Nature Medicine.
They cleaned the text by removing hashtags, Twitter handles, HTML tags, emojis, and links to websites, the researchers noted.
The final OpenPath dataset included:
116,504 image-text pairs from Twitter posts,
59,869 from replies, and
32,041 image-text pairs scraped from the internet or obtained from the LAION dataset.
The latter is an open-source database from Germany that can be used to train text-to-image AI software such as Stable Diffusion.
Training the PLIP AI Platform
Once they had the dataset, the next step was to train the PLIP AI model. This required a technique known as contrastive learning, the researchers wrote, in which the AI learns to associate features from the images with portions of the text.
As explained in Baeldung, an online technology publication, contrastive learning is based on the idea that “it is easier for someone with no prior knowledge, like a kid, to learn new things by contrasting between similar and dissimilar things instead of learning to recognize them one by one.”
“The power of such a model is that we don’t tell it specifically what features to look for. It’s learning the relevant features by itself,” Zou said in the SCOPE blog post.
The resulting AI PLIP tool will enable “a clinician to input a new image or text description to search for similar annotated images in the database—a sort of Google Image search customized for pathologists,” SCOPE explained.
“Maybe a pathologist is looking at something that’s a bit unusual or ambiguous,” Zou told SCOPE. “They could use PLIP to retrieve similar images, then reference those cases to help them make their diagnoses.”
The Stanford University researchers continue to collect pathology images from X. “The more data you have, the more it will improve,” Zou said.
Pathologists will want to keep an eye on the Stanford Medicine research team’s progress. The PLIP AI tool may be a boon to diagnostics and improve patient outcomes and care.
In a handful of cases, health insurers reversed denials after physicians or patients posted complaints on social media
Prior authorization requirements by health insurers have long been a thorn in the side of medical laboratories, as well as physicians. But now, doctors and patients are employing a new tactic against the practice—turning to social media to shame payers into reversing denials, according to KFF Health News (formerly Kaiser Health News).
Genetic testing lab companies are quite familiar with prior authorization problems. They see a significant number of their genetic test requests fail to obtain a prior authorization. Thus, if the lab performs the test, the payer will likely not reimburse, leaving the lab to bill the patient for 100% of the test price, commonly $1,000 to $5,000. Then, an irate patient typically calls the doctor to complain about the huge out-of-pocket cost.
“There are times when you simply must call out wrongdoings,” she wrote in an Instagram post, according to the outlet. “This is one of those times.”
In response, an “escalation specialist” from BCBSIL contacted her but was unable to help. Then, after KFF Health News reached out, Nix discovered on her own that $36,000 in outstanding claims were marked “paid.”
“No one from the company had contacted her to explain why or what had changed,” KFF reported. “[Nix] also said she was informed by her hospital that the insurer will no longer require her to obtain prior authorization before her infusions, which she restarted in July.”
“I think we’re on the precipice of really improving the environment for prior authorization,” said Todd Askew, Senior Vice President, Advocacy, for the American Medical Association, in an AMA Advocacy Update. If this was to happen, it would be welcome news for clinical laboratories and anatomic pathology groups. (Photo copyright: Nashville Medical News.)
Physicians Also Take to Social Media to Complain about Denials
Some physicians have taken similar actions, KFF Health News reported. One was gastroenterologist Shehzad A. Saeed, MD, of Dayton Children’s Hospital in Ohio. Saeed posted a photo of a patient’s skin rash on Twitter in March after Anthem denied treatment for symptoms of Crohn’s disease. “Unacceptable and shameful!” he tweeted.
Two weeks later, he reported that the treatment was approved soon after the tweet. “When did Twitter become the preferred pathway for drug approval?” he wrote.
Eunice Stallman, MD, a psychiatrist from Boise, Idaho, complained on X (formerly Twitter) about Blue Cross of Idaho’s prior authorization denial of a brain cancer treatment for her nine-month-old daughter. “This is my daughter that you tried to deny care for,” she posted. “When a team of expert [doctors] recommend a treatment, your PharmD reviewers don’t get to deny her life-saving care for your profits.”
However, in this case, she posted her account after Blue Cross Idaho reversed the denial. She said she did this in part to prevent the payer from denying coverage for the drug in the future. “The power of the social media has been huge,” she told KFF Health News. The story noted that she joined X for the first time so she could share her story.
Affordable Care Act Loophole?
“We’re not going to get rid of prior authorization. Nobody is saying we should get rid of it entirely, but it needs to be right sized, it needs to be simplified, it needs to be less friction between the patient and accessing their benefits. And I think we’re on really good track to make some significant improvements in government programs, as well as in the private sector,” said Todd Askew, Senior Vice President, Advocacy, for the American Medical Association, in an AMA Advocacy Update.
However, KFF HealthNews reported that Kaye Pestaina, JD, a Kaiser Family Foundation VP and Co-Director of the group’s Program on Patient and Consumer Protections, noted that some “patient advocates and health policy experts” have questioned whether payers’ use of prior authorization denials may be a way to get around the Affordable Care Act’s prohibition against denial of coverage for preexisting conditions.
“They take in premiums and don’t pay claims,” family physician and healthcare consultant Linda Peeno, MD, told KFF Health News. “That’s how they make money. They just delay and delay and delay until you die. And you’re absolutely helpless as a patient.” Peeno was a medical reviewer for Humana in the 1980s and then became a whistleblower.
The issue became top-of-mind for genetic testing labs in 2017, when Anthem (now Elevance) and UnitedHealthcare established programs in which physicians needed prior authorization before the insurers would agree to pay for genetic tests.
Dark Daily’s sister publication The Dark Report covered this in “Two Largest Payers Start Lab Test Pre-Authorization.” We noted then that it was reasonable to assume that other health insurers would follow suit and institute their own programs to manage how physicians utilize genetic tests.
At least one large payer has made a move to reduce prior authorization in some cases. Effective Sept. 1, UnitedHealthcare began a phased approach to remove prior authorization requirements for hundreds of procedures, including more than 200 genetic tests under some commercial insurance plans.
However, a source close to the payer industry noted to Dark Daily that UnitedHealthcare has balked at paying hundreds of millions’ worth of genetic claims going back 24 months. The source indicated that genetic test labs are engaging attorneys to push their claims forward with the payer.
Is Complaining on Social Media an Effective Tactic?
A story in Harvard Business Review cited research suggesting that companies should avoid responding publicly to customer complaints on social media. Though public engagement may appear to be a good idea, “when companies responded publicly to negative tweets, researchers found that those companies experienced a drop in stock price and a reduction in brand image,” the authors wrote.
However, the 2023 “National Customer Rage Survey,” conducted by Customer Care Measurement and Consulting and Arizona State University, found that nearly two-thirds of people who complained on social media received a response. And “many patients and doctors believe venting online is an effective strategy, though it remains unclear how often this tactic works in reversing prior authorization denials,” KFF Health News reported.
Federal Government and States Step In
KFF Health News reported that the federal government is proposing reforms that would require some health plans “to provide more transparency about denials and to speed up their response times.” The changes, which would take effect in 2026, would apply to Medicaid, Medicare Advantage, and federal Health Insurance Marketplace plans, “but not employer-sponsored health plans.”
KFF also noted that some insurers are voluntarily revising prior authorization rules. And the American Medical Association reported in March that 30 states, including Arkansas, California, New Jersey, North Carolina, and Washington, are considering their own legislation to reform the practice. Some are modeled on legislation drafted by the AMA.
Though the states and the federal government are proposing regulations to address prior authorization complaints, reform will likely take time. Given Harvard Business Review’s suggestion to resist replying to negative customer complaints in social media, clinical labs—indeed, all healthcare providers—should carefully consider the full consequences of going to social media to describe issues they are having with health insurers.
Some healthcare experts point to an “immunity gap” tied to the COVID-19 pandemic, while others suggest alternative theories such as temporary immunodeficiency brought on by COVID-19. In most cases, RSV causes “mild, cold-like symptoms,” but the CDC states it also can cause serious illness, especially for infants, young children, and older adults, leading to emergency room visits, hospitalizations, and an increased demand for clinical laboratory testing.
Pulmonology Advisor reported that the disease typically peaks between December and February, but hospitalizations this season hit their peak in November with numbers far higher than in previous years. In addition to infants and older adults, children between five and 17 years of age were “being hospitalized far in excess of their numbers in previous seasons,” the publication reported.
“Age by itself is a risk factor for more severe disease, meaning that the younger babies are usually the ones that are sick-sick,” pediatrician Asuncion Mejias, MD, PhD (above), a principal investigator with the Center for Vaccines and Immunity at Nationwide Children’s Hospital in Columbus, Ohio, told MarketWatch. Now, she added, “we are also seeing older kids, probably because they were not exposed to RSV the previous season.” Clinical laboratories in hospitals caught the brunt of those RSV inpatient admissions. (Photo copyright: Nationwide Children’s Hospital.)
Did COVID-19 Cause Immunity Gap and Surge in Respiratory Diseases?
CDC data shows that hospitalization rates linked to RSV have steadily declined since hitting their peak of 5.2 per 100,000 people in mid-November. In contrast, hospitalizations linked to the flu peaked in late November and early December at 8.7 per 100,000. Hospitalizations linked to COVID 19—which still exceed those of the other respiratory diseases—reached a plateau of 9.7 per 100,000 in early December, then saw an uptick later that month before declining in the early part of January, 2023, according to the CDC’s Respiratory Virus Hospitalization Surveillance Network (RESP-NET) dashboard.
Surveillance by the CDC’s National Center for Immunization and Respiratory Diseases (NCIRD) revealed a similar pattern: An early peak in weekly numbers for emergency room visits for RSV, followed by a spike for influenza and steadier numbers for COVID-19.
So, why was the RSV outbreak so severe?
Respiratory diseases tend to hit hardest in winter months when people are more likely to gather indoors. Beyond that, some experts have cited social distancing and masking requirements imposed in 2020 and 2021 to limit the spread of COVID 19. These measures, along with school closures, had the side effect of reducing exposure to influenza and RSV.
“It’s what’s being referred to as this ‘immunity gap’ that people have experienced from not having been exposed to our typical respiratory viruses for the last couple of years, combined with reintroduction to indoor gatherings, indoor venues, indoor school, and day care without any of the mitigation measures that we had in place for the last couple of years,” infectious disease expert Kristin Moffitt, MD, of Boston Children’s Hospital told NPR.
Term ‘Immunity Debt’ Sparks Controversy
Other experts have pushed back against the notion that pandemic-related public health measures are largely to blame for the RSV upsurge. Many have objected to the term “immunity debt,” a term Forbes reported on in November.
“Immunity debt is a made-up term that did not exist until last year,” pediatrician Dave Stukus, MD, wrote on Twitter. Stukus is a Professor of Clinical Pediatrics in the Division of Allergy and Immunology at Nationwide Children’s Hospital in Columbus, Ohio.
An article published by Texas Public Radio (TPR) suggests further grounds for skepticism, stating that “the immunity debt theory doesn’t seem to hold up to scrutiny.”
“That was sort of the great unmasking, and everybody got viral illnesses,” she told TPR. “Now we’re past that. We’ve already been through that. We should have some immunity from that and we’re having it again.”
She added that “the hospital is filled with babies who are less than a year of age who have RSV infection. Those children weren’t locked down in 2020.”
The story also noted that not all Americans complied with social distancing or masking guidelines.
“We’re not seeing [less viral illness in] states in the United States that were less strict compared to states that were stricter during mask mandates and things like that. All the states are being impacted,” Barton told TPR.
Perfect Storm of Demand for Clinical Laboratory Testing
Barton suggested that COVID-19 might have compromised people’s immune systems in ways that made them more susceptible to other respiratory diseases. For example, a study published in Nature Immunology, titled, “Immunological Dysfunction Persists for Eight Months following Initial Mild-to-Moderate SARS-CoV-2 Infection,” found that some patients who survived COVID-19 infection developed post-acute long COVID (LC, aka, COVID syndrome) which lasted longer than 12 weeks. And that “patients with LC had highly activated innate immune cells, lacked naive T and naive B cells, and showed elevated expression of type I IFN (IFN-β) and type III IFN (IFN-λ1) that remained persistently high at eight months after infection.”
Experts speaking to The Boston Globe said that multiple factors are likely to blame for the severity and early arrival of the RSV outbreak. Pediatric hospitalist and infectious disease specialist Chadi El Saleeby, MD, of Massachusetts General Hospital, said the severity of some cases might be tied to simultaneous infection with multiple viruses.
Clinical laboratories experienced a perfect storm of infectious disease testing demands during this tripledemic. Hopefully, with the arrival of spring and summer, that demand for lab tests will wane and allow for a return to a normal rate of traditional laboratory testing.
Protecting patient privacy is of critical importance, and yet researchers reidentified data using only a few additional data points, casting doubt on the effectiveness of existing federally required data security methods and sharing protocols
Therefore, recent coverage in The Guardian which reported on how easily so-called “deidentified data” can be reidentified with just a few additional data points should be of particular interest to clinical laboratory and health network managers and stakeholders.
“We found that patients can be re-identified, without decryption, through a process of linking the unencrypted parts of the record with known information about the individual such as medical procedures and year of birth,” Culnane stated in a UM news release. “This shows the surprising ease with which de-identification can fail, highlighting the risky balance between data sharing and privacy.”
In a similar study published in Scientific Reports, Yves-Alexandre de Montjoye, PhD, a computation private researcher, used location data on 1.5 million people from a mobile phone dataset collected over 15 months to identify 95% of the people in an anonymized dataset using four unique data points. With just two unique data points, he could identify 50% of the people in the dataset.
“Location data is a fingerprint. It’s a piece of information that’s likely to exist across a broad range of data sets and could potentially be used as a global identifier,” Montjoye told The Guardian.
The problem is exacerbated by the fact that everything we do online these days generates data—much of it open to the public. “If you want to be a functioning member of society, you have no ability to restrict the amount of data that’s being vacuumed out of you to a meaningful level,” Chris Vickery, a security researcher and Director of Cyber Risk Research at UpGuard, told The Guardian.
This privacy vulnerability isn’t restricted to just users of the Internet and social media. In 2013, Latanya Sweeney, PhD, Professor and Director at Harvard’s Data Privacy Lab, performed similar analysis on approximately 579 participants in the Personal Genome Project who provided their zip code, date of birth, and gender to be included in the dataset. Of those analyzed, she named 42% of the individuals. Personal Genome Project later confirmed 97% of her submitted names according to Forbes.
In testimony before the Privacy and Integrity Advisory Committee of the Department of Homeland Security (DHS), Latanya Sweeney, PhD (above), Professor and Director at Harvard’s Data Privacy Lab stated, “One problem is that people don’t understand what makes data unique or identifiable. For example, in 1997 I was able to show how medical information that had all explicit identifiers, such as name, address and Social Security number removed could be reidentified using publicly available population registers (e.g., a voter list). In this particular example, I was able to show how the medical record of William Weld, the Governor of Massachusetts of the time, could be reidentified using only his date of birth, gender, and ZIP. In fact, 87% of the population of the United States is uniquely identified by date of birth (e.g., month, day, and year), gender, and their 5-digit ZIP codes. The point is that data that may look anonymous is not necessarily anonymous. Scientific assessment is needed.” (Photo copyright: US Department of Health and Human Services.)
“Open publication of deidentified records like health, census, tax or Centrelink data is bound to fail, as it is trying to achieve two inconsistent aims: the protection of individual privacy and publication of detailed individual records,” Dr. Teague noted in the UM news release. “We need a much more controlled release in a secure research environment, as well as the ability to provide patients greater control and visibility over their data.”
While studies are mounting to show how vulnerable deidentified information might be, there’s little in the way of movement to fix the issue. Nevertheless, clinical laboratories should consider carefully any decision to sell anonymized (AKA, blinded) patient data for data mining purposes. The data may still contain enough identifying information to be used inappropriately. (See Dark Daily, “Coverage of Alexion Investigation Highlights the Risk to Clinical Laboratories That Sell Blinded Medical Data,” June 21, 2017.)
Should regulators and governments address the issue, clinical laboratories and healthcare providers could find more stringent regulations on the sharing of data—both identified and deidentified—and increased liability and responsibility regarding its governance and safekeeping.
Until then, any healthcare professional or researcher should consider the implications of deidentification—both to patients and businesses—should people use the data shared in unexpected and potentially malicious ways.
