Lead author of a new study, Ciro Chiappini, PhD, says this new technology could lead to advancements in personalized medicine
Scientists at King’s College London have developed a nanoneedle patch that offers a painless alternative to biopsies that also delivers quicker and more accurate results.
As reported by Phys Org, new research published in Nature Nanotechnology shows that these new patches could be the future of diagnostics. As common as traditional biopsies are, they can be painful and often patients are deterred from follow-ups as well as seeking out treatment and early diagnosis.
“We have been working on nanoneedles for twelve years, but this is our most exciting development yet. It opens a world of possibilities for people with brain cancer, Alzheimer’s, and for advancing personalized medicine. It will allow scientists—and eventually clinicians—to study disease in real time like never before.” said Ciro Chiappini, PhD, senior lecturer at King’s College London and lead author of the study.
The lead author of the study, Ciro Chiappini, PhD, senior lecturer at King’s College London said the new development doesn’t disrupt the cell membrane in a way that cannot be repaired. (Photo copyright: King’s College London)
How it Works
The patches are made up of tens of millions of microscopic needles that are 1,000 times thinner than a human hair and do not remove tissue. This causes no damage and pain while the nanoneedles extract molecular fingerprints from the tissue. The sample is then analyzed using both mass spectrometry and artificial intelligence.
“This approach provides multidimensional molecular information from different types of cells within the same tissue. Traditional biopsies simply cannot do that. And because the process does not destroy the tissue, we can sample the same tissue multiple times, which was previously impossible.” said Chiappini of the process. The study focused on lipids and applied the patch to brain cancer tissue of human origin and mice.
Potential Limitations
Additional reporting by Science News looks into some of the possible drawbacks of the technology.
The patch can’t sample tissue that exists deeper in the body, yet Chiappini says that physicians can use the patch during surgery to get fast results on tissue they are operating on. “It’s very much a surface technology, which is potentially [both] a limitation and a feature,” he says.
Phys Org explained the potential during brain surgery. A surgeon would apply a patch to a “suspicious area” and receive results within 20 minutes, providing the surgical team with impactful information in real-time.
Less Pain, More Gain?
It is no secret that patients will often try to avoid or put off uncomfortable medical procedures like biopsies. This new development is part of an ongoing larger trend—making medical procedures more appealing to encourage higher percentages of patients to seek care and receive treatment. As recently reported by Dark Daily in the article entitled, “University of Texas Study Shows Self-Collection Boosts Cancer Screenings among Women,” a new at-home collection kit to replace a traditional Pap smear may help boost early detection of cervical cancer in women.
This new technology and trend toward less painful procedures suggests that patients will be more inclined to participate in pathology exams if they were less invasive and uncomfortable or painful. Pathology professionals should keep on eye on future developments in this space.
Biopsies are not yet ready to become obsolete, as the patch is still in its early stages and more research is needed.
Scientists suspect that the plastics can be linked to a host of medical conditions, but clear evidence is elusive without appropriate biomarkers for clinical laboratory testing
Recent research indicates that microplastics and nanoplastics (MNPs) are accumulating in human organs at an increasing rate. The health impact is not entirely clear, but the research suggests that clinical laboratories could someday find themselves testing for levels of MNPs in patients.
In one study, scientists at the University of New Mexico and Oklahoma State University analyzed autopsy samples of liver, kidney, and frontal cortex brain tissue collected in 2016 and 2024. “Brains exhibited higher concentrations of MNPs than liver or kidney samples,” they wrote. However, “all organs exhibited significant increases from 2016 to 2024.”
“The concentrations we saw in the brain tissue of normal individuals, who had an average age of around 45 or 50 years old, were 4,800 micrograms per gram, or 0.5% by weight,” lead author Matthew Campen, PhD, Regents’ Professor, Pharmaceutical Sciences, University of New Mexico, and Director of the New Mexico Center for Metals in Biology and Medicine (CMBM), told CNN. “Compared to autopsy brain samples from 2016, that’s about 50% higher.”
Researchers have not yet uncovered clear evidence of specific health risks, but “what scientists worry about is several trends in disease prevalence that have been unexplained—Alzheimer’s disease and dementia, colorectal cancer in people under 50, inflammatory bowel disease, and global reductions in sperm count,” Campen told Everyday Health.
In another recent study, a different team of researchers at the University of New Mexico found high levels of microplastics in human and canine testicular tissue.
“At the beginning, I doubted whether microplastics could penetrate the reproductive system,” said lead author Xiaozhong Yu, MD, PhD, Professor, University of New Mexico College of Nursing in a university news story. “When I first received the results for dogs I was surprised. I was even more surprised when I received the results for humans.”
“The rate of increase in microplastics in the environment is exponential and we have every reason to believe that the concentrations in our bodies will continue to increase in the coming years and decades,” Matthew Campen, PhD (above), of the University of New Mexico told Everyday Health. As studies continue to produce evidence that nanoplastics affect human health, testing companies may develop biomarkers for clinical laboratory tests that measure the amount of microplastics in different organ locations. (Photo copyright: University of New Mexico.)
Landrigan told CNN that most people are exposed to MNPs through their diet, “but inhalation is also an important route.”
However, he added, “it’s important not to scare the hell out of people, because the science in this space is still evolving, and nobody in the year 2024 is going to live without plastic.”
CNN noted that experts consider nanoplastics to be the biggest concern [as opposed to microplastics] because they can infiltrate human cells.
“Somehow these nanoplastics hijack their way through the body and get to the brain, crossing the blood-brain barrier,” Campen told CNN. “Plastics love fats, or lipids, so one theory is that plastics are hijacking their way with the fats we eat which are then delivered to the organs that really like lipids—the brain is top among those.”
The US Food and Drug Administration (FDA) states that microplastics typically measure less than 5mm, whereas nanoplastics are less than a micron (micrometer). However, the agency notes that “there are currently no standard definitions for the size of microplastics or nanoplastics.”
What Are the Health Risks?
Scientists suspect that MNPs could be associated with cancer, cardiovascular disease, kidney disease, Alzheimer’s disease, and infertility, The Washington Post reported, but that they “still don’t have a clear sense of what these materials are doing to the human body.”
“In a 2021 study, researchers in Switzerland identified more than 10,000 chemicals used in the manufacture of plastic—of which over 2,400 were potentially ‘of concern’ for human health,” The Post noted.
“To be able to say we have a health impact, we need to have a direct correlation between a product and a health outcome,” Phoebe Stapleton, PhD, Associate Professor at the Rutgers University Ernest Mario School of Pharmacy (EMSOP), told The Post. “It’s very narrow, that straight line. And there’s so many different health outcomes there could be, and we’re finding these particles in so many different tissues.”
One study published in the New England Journal of Medicine (NEJM) suggested that MNPs in arteries could be risk factors for heart attacks or strokes. But even here, the authors wrote, “direct evidence that this risk extends to humans is lacking.”
Yu suspects that MNPs could be a factor in a global decline in sperm count, along with other environmental contaminants such as heavy metals and pesticides. His study found that polyethylene was the most prevalent plastic in dogs, followed by polyvinyl chloride (PVC). Higher levels of PVC correlated with lower sperm count, but there was no correlation with polyethylene.
“PVC can release a lot of chemicals that interfere with spermatogenesis, and it contains chemicals that cause endocrine disruption,” he said in the UNM news story.
Clinical laboratory managers should recognize that interest in identifying micro- and nanoplastics in every organ of the human body will increase. At some point, physicians may want labs to test their patients for microplastic levels in certain organ sites. This will likely be when enough published studies show a correlation between high levels of microplastics in certain locations of the body and specific disease states.
Biomarker may lead to clinical laboratory testing that enables clinical pathologists and urologists to diagnose risk for diabetic kidney failure years before it occurs
Clinical laboratories working with nephrologists and urologists to diagnose patients experiencing urinary system difficulties know that albumin (excessive protein found in the urine) is a common biomarker used in clinical laboratory testing for kidney disease. But patients with diabetes generally have low protein in their urine due to that disease. Thus, it is difficult to diagnose early stage kidney failure in diabetic patients.
But now, researchers at the University of Texas Health Science Center at San Antonio (UT Health San Antonio) have discovered a biomarker called adenine (also found in the urine) which, they say, offers the ability to diagnose diabetic patients at risk of kidney failure significantly earlier than other biomarkers.
A UT Health San Antonio news release states, “Urine levels of adenine, a metabolite produced in the kidney, are predictive and a causative biomarker of looming progressive kidney failure in patients with diabetes, a finding that could lead to earlier diagnosis and intervention.”
The study’s senior author Kumar Sharma, MD, professor and Chief of Nephrology at UT Health San Antonio, said, “The finding paves the way for clinic testing to determine—five to 10 years before kidney failure—that a patient is at risk.”
“The study is remarkable as it could pave the way to precision medicine for diabetic kidney disease at an early stage of the disease,” said study lead Kumar Sharma, MD (above), professor and Chief of Nephrology at UT Health San Antonio, in a news release. This would be a boon to clinical laboratories and pathology groups that work with urologists to diagnose and treat diabetic patients who are at-risk for kidney failure. (Photo copyright: UT Health San Antonio.)
Completing the UT Health Study
Sharma and his team worked for five years to discover that the adenine molecule was damaging kidney tissue, News4SA reported. The research required the team to develop new methods for viewing small molecules known as metabolites.
“UT Health San Antonio is one of few centers in the US perfecting a technique called spatial metabolomics on kidney biopsies from human patients,” the news release notes. The kidney biopsies were obtained through the Kidney Precision Medicine Project (KPMP) and were gathered from various US academic centers.
“It’s a very difficult technique, and it took us several years to develop a method where we combine high resolution of the geography of the kidney with mass spectrometry analysis to look at the metabolites,” Sharma said.
Testing by the UT Health team unearthed “endogenous adenine around scarred blood vessels in the kidney and around tubular-shaped kidney cells that were being destroyed. Endogenous substances are those that naturally occur in the body,” the news release notes.
Findings Could Affect Diabetic Care
UT Health San Diego’s study findings could allow for early intervention and change the way diabetes care is managed, Sharma said.
“The study results are significant because until now, the most important marker for kidney disease has been protein (or albumin) in the urine. Up to half of diabetes patients who develop kidney failure never have much protein in their urine. As 90% of patients with diabetes (more than 37 million patients in the US) remain at increased risk despite low levels of albumin in their urine, this study has widespread consequences. It is the first study to identify these patients at an early stage by measuring this new causative marker in the urine,” the UT Health news release states.
“We’re hoping that by identifying patients early in their course, and with new therapies targeting adenine and kidney scarring, we can block kidney disease or extend the life of the kidney much longer,” Sharma said.
Getting Ahead of Kidney Disease
Though many patients recognize their risk for kidney disease, those who do not have protein in their urine may not take the risk seriously enough, Sharma noted.
“They could be feeling a false sense of security that there is no kidney disease occurring in their body, but in fact, in many cases it is progressing, and they often don’t find out until the kidney disease is pretty far advanced. And at that time, it is much harder to protect the kidneys and prevent dialysis,” he said in the new release.
“Once a patient needs dialysis, he or she must have a fistula or catheter placed and go on a dialysis machine three times a week, four hours at a time to clean the blood,” the news release states.
“The death rate is very high, especially in patients with diabetes,” Sharma added. “There is about 40% mortality within five years in patients with diabetes and kidney failure.”
Though measuring adenine in urine is a challenge, Sharma and his team developed a method that can be performed at UT Health San Antonio on at-risk patients with a doctor’s order. The test results go back to the patient’s doctor.
“The test is being approved for clinical use and right now it is an experimental test, but we expect it to be available for all patients in the near future.” Sharma told News4SA.
“What we’re hoping is that by identifying patients early in their course, and with new therapies targeting adenine and kidney scarring, we can block kidney disease or extend the life of the kidney much longer,” Sharma said in the news release.
And so, thanks to the UT Health researchers, pathologists and clinical laboratories may soon see a new diagnostic test biomarker that will help urologists identify diabetic patients at-risk for kidney failure years earlier than previously possible.
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.
New artificial intelligence model agrees with interpretations of human medical technologists and microbiologists with extraordinary accuracy
Microbiology laboratories will be interested in news from Brescia University in Italy, where researchers reportedly have developed a deep learning model that can visually identify and analyze bacterial species in culture plates with a high level of agreement with interpretations made by medical technologists.
They initially trained and tested the system to digitally identify pathogens associated with urinary tract infections (UTIs). UTIs are the source for a large volume of clinical laboratory microbiological testing.
The system, known as DeepColony, uses hierarchical artificial intelligence technology. The researchers say hierarchical AI is better suited to complex decision-making than other approaches, such as generative AI.
In their Nature paper, the researchers explained that microbiologists use conventional methods to visually examine culture plates that contain bacterial colonies. The scientists hypothesize which species of bacteria are present, after which they test their hypothesis “by regrowing samples from each colony separately and then employing mass spectroscopy techniques,” to confirm their hypotheses.
However, DeepColony—which was designed for use with clinical laboratory automation systems—looks at high-resolution digital scans of cultured plates and attempts to identify the bacterial strains and analyze them in much the same way a microbiologist would. For example, it can identify species based on their appearance and determine which colonies are suitable for analysis, the researchers explained.
“Working on a large stream of clinical data, and a complete set of 32 pathogens, the proposed system is capable of effectively assisting plate interpretation with a surprising degree of accuracy in the widespread and demanding framework of urinary tract infections,” the study authors wrote. “Moreover, thanks to the rich species-related generated information, DeepColony can be used for developing trustworthy clinical decision support services in laboratory automation ecosystems from local to global scale.”
“Compared to the most common solutions based on single convolutional neural networks (CNN), multi-network architectures are attractive in our case because of their ability to fit into contexts where decision-making processes are stratified into a complex structure,” wrote the study’s lead author Alberto Signoroni, PhD (above), Associate Professor of Computer Science, University of Brescia, and his researcher team in their Nature paper. “The system must be designed to generate useful and easily interpretable information and to support expert decisions according to safety-by-design and human-in-the-loop policies, aiming at achieving cost-effectiveness and skill-empowerment respectively.” Microbiologists and clinical laboratory managers will want to follow the further development of this technology. (Photo copyright: University of Brescia.)
How Hierarchical AI Works
Writing in LinkedIn, patent attorney and self-described technology expert David Cain, JD, of Hauptman Ham, LLP, explained that hierarchical AI systems “are structured in layers, each with its own distinct role yet interconnected in a way that forms a cohesive whole. These systems are significant because they mirror the complexity of human decision-making processes, incorporating multiple levels of analysis and action. This multi-tiered approach allows for nuanced problem-solving and decision-making, akin to a seasoned explorer deftly navigating through a multifaceted terrain.”
DeepColony, the researchers wrote, consists of multiple convolutional neural networks (CNNs) that exchange information and cooperate with one another. The system is structured into five levels—labeled 0 through 4—each handling a different part of the analysis:
At level 0, the system determines the number of bacterial colonies and their locations on the plate.
At level 1, the system identifies “good colonies,” meaning those suitable for further identification and analysis.
At level 2, the system assigns each good colony to a bacterial species “based on visual appearance and growth characteristics,” the researchers wrote, referring to the determination as being “pathogen aware, similarity agnostic.”
The CNN used at this stage was trained by using images of 26,213 isolated colonies comprising 32 bacterial species, the researchers wrote in their paper. Most came from clinical laboratories, but some were obtained from the American Type Culture Collection (ATCC), a repository of biological materials and information resources available to researchers.
At level 3, the system attempts to improve accuracy by looking at the larger context of the plate. The goal here is to “determine if observed colonies are similar (pure culture) or different (mixed cultures),” the researchers wrote, describing this step as “similarity aware, pathogen agnostic.” This enables the system to recognize variants of the same strain, the researchers noted, and has the effect of reducing the number of strains identified by the system.
At this level, the system uses two “Siamese CNNs,” which were trained with a dataset of 200,000 image pairs.
Then, at level 4, the system “assesses the clinical significance of the entire plate,” the researchers added. Each plate is labeled as:
“Positive” (significant bacterial growth),
“No significant growth” (negative), or
“Contaminated,” meaning it has three or more “different colony morphologies without a particular pathogen that is prevalent over the others,” the researchers wrote.
If a plate is labeled as “positive,” it can be “further evaluated for possible downstream steps,” using MALDI-TOF mass spectrometry or tests to determine susceptibility to antimicrobial measures, the researchers stated.
“This decision-making process takes into account not only the identification results but also adheres to the specific laboratory guidelines to ensure a proper supportive interpretation in the context of use,” the researchers wrote.
Nearly 100% Agreement with Medical Technologists
To gauge DeepColony’s accuracy, the researchers tested it on a dataset of more than 5,000 urine cultures from a US laboratory. They then compared its analyses with those of human medical technologists who had analyzed the same samples.
Agreement was 99.2% for no-growth cultures, 95.6% for positive cultures, and 77.1% for contaminated or mixed growth cultures, the researchers wrote.
The lower agreement for contaminated cultures was due to “a deliberately precautionary behavior, which is related to ‘safety by design’ criteria,” the researchers noted.
Lead study author Alberto Signoroni, PhD, Associate Professor of Computer Science, University of Brescia, wrote in Nature that many of the plates identified by medical technologists as “contaminated” were labeled as “positive” by DeepColony. “We maximized true negatives while allowing for some false positives, so that DeepColony [can] focus on the most relevant or critical cases,” he said.
Will DeepColony replace medical technologists in clinical laboratories any time soon? Not likely. But the Brescia University study indicates the direction AI in healthcare is headed, with high accuracy and increasing speed. The day may not be far off when pathologists and microbiologists regularly employ AI algorithms to diagnose disease.
