It’s why Jaws swam out of sight for more than an hour and hints at the glamour of giftwrap. In movie theaters, living rooms, and even labs, the thrill of the unseen can be counted on to keep us guessing. But when it comes to the hidden chemical world of cells, scientists need no longer wonder.

Inspired by this same thrill, researchers at the Beckman Institute for Advanced Science and Technology developed an innovative way to ‘see’ the fine structure and chemical composition of a human cell with unmatched clarity and precision. Their technique, which appeared in PNAS earlier this week, takes a creative — and counterintuitive — approach to signal detection.

“Biology is one of the most exciting sciences of our time because there has always been a divide between what we can see and what we cannot see,” said Rohit Bhargava, a professor of bioengineering at the University of Illinois Urbana-Champaign who led the study.

As the smallest functional units in our bodies, cells have long commanded the attention of researchers interested in determining what they’re made of and where each element resides. Together, the “what” and the “where” form an all-purpose cellular blueprint that can be used to study biology, chemistry, materials, and more.

Before this study, obtaining a high-resolution copy of that blueprint ranked among the impossible.

“Now, we can see inside cells in a much finer resolution and with significant chemical detail more easily than ever,” Bhargava said. “This work opens a range of possibilities, including a new way to examine the combined chemical and physical aspects that govern human development and disease.”

The researchers’ work builds on prior strides in the field of chemical imaging.

Whereas optical microscopy uses visible light to illuminate surface-level features like color and structure, chemical imaging uses invisible infrared light to reveal a sample’s inner workings.

When a cell is exposed to IR light, its temperature rises, and it expands. We know from night vision goggles that no two objects absorb IR wavelengths in exactly the same way; comparing a poodle to a park bench is evidence enough that warmer objects emit stronger IR signatures than cooler ones. The same is true inside a cell, where each type of molecule absorbs IR light at a subtly different wavelength and emits a unique chemical signature. Examining the absorption patterns — a method called spectroscopy — allows researchers to pinpoint the whereabouts of each.

Unlike night vision goggles, the researchers do not analyze the absorption patterns as a color spectrum. Instead, they interpret the IR waves with a signal detector: a minute beam fastened to the microscope on one end, with a fine tip that scrapes the cell’s surface like the nanoscale needle of a record player.

Innovations in spectroscopy over the last decade have focused on steadily increasing the strength of the initial IR wavelengths.

“It’s an intuitive approach because we are conditioned to think of larger signals as being better. We think, ‘The stronger the IR signal, the higher a cell’s temperature becomes, the more it expands, and the easier it will be to see,'” Bhargava said.

A sizeable setback is hidden within this approach. As the cell expands, the motion of the signal detector becomes more exaggerated and generates “noise”: so-called static that impedes accurate chemical measurements.

“It’s like turning up the dial on a staticky radio station — the music gets louder, but so does the static,” said Seth Kenkel, a postdoctoral researcher in Professor Bhargava’s lab and the study’s lead author.

In other words, no matter how powerful the IR signal became, the quality of the chemical imaging could not advance.

“We needed a solution to stop the noise from increasing alongside the signal,” Kenkel said.

The researchers’ remedy to noisy cellular imaging works by divorcing the IR signal from the detector’s movement, allowing for amplification without the added noise.

Instead of focusing their energies on the strongest possible IR signal, the researchers began by experimenting with the smallest signal they could manage, ensuring that they could effectively implement their solution before upping the strength. Though “counterintuitive,” according to Kenkel, starting small allowed the researchers to honor a decade of spectroscopy research and lay critical groundwork for the future of the field.

Bhargava likens the approach to a road trip gone awry.

“Imagine that spectroscopy researchers were in a car, headed to the Grand Canyon. Of course, everyone would think that the faster the car moves, the faster they’ll reach the destination. But the problem is that the car is headed east from Urbana,” he said.

Increasing the hypothetical car’s speed is analogous to strengthening the IR signal.

“We pulled over, looked at a map, and pointed the car in the correct direction. Now, the increased speed — the increased signal — can effectively move the field forward.”

The researchers’ “map” enables high-resolution chemical and structural imaging of cells at the nanoscale — a scale 100,000 times smaller than a strand of hair. Notably, this technique is free of fluorescent labeling, or dyeing molecules to increase their visibility under a microscope.

While the facilities in Beckman’s Microscopy Suite were critical to the study’s experimental stage, the idea itself arose not from sophisticated technology, but from a culture that supported curiosity, unconventional problem-solving, and diverse perspectives.

“This is why the Beckman Institute is an amazing place,” Bhargava said. “This project needed ideas from spectroscopy, from mechanical engineering, from signal processing, and of course biology. You can’t combine these fields seamlessly anywhere other than Beckman. This study is a classic example of Beckman’s blend of interdisciplinary science at the cutting edge of advanced science and technology.”

Research reported in this press release was supported in part by the National Institute of Biomedical Imaging and Bioengineering of the National Institutes of Health under award numbers T32EB019944 and R01EB009745, as well as the National Science Foundation under award number 2153032. This content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

His latest project created an algorithm that can predict and measure the incompleteness of electronic health records — in everything from your lab results to disease diagnoses, medical history to prescription records.

Missing information in the electronic health records (EHR) that hospitals and doctor’s offices keep is like a leaking pipe, he says. If you don’t know where the leak is, you can’t fix it, and soon the house can flood. The same dangers can happen in healthcare. A recent study by Gurupur revealed that a critical percent of digital health records contained missing information.

His algorithm uses mathematics and computer science to answer, “Where is the water leaking?” he says. The analysis performed by Gurupur and his team found that the level of incompleteness per year varies and there is not a pattern of where missing data happens. His algorithm helps identify attributes that have a higher tendency to be incomplete — the areas of the water pipe that are more vulnerable and can break more frequently.

His previous studies have documented that the biggest reasons for missing health information are communication and education. Communication between patients and their providers isn’t always clear — especially if the patient is interacting with a healthcare professional who does not speak their native language. Cultural barriers may keep patients from sharing important information with their providers. Digital technology also creates its own challenges. Providers may not fill out electronic records until day’s end — and forget what the patient said or not have it accurately in their notes. Hospitals and clinics switch electronic health record systems, requiring extensive new retraining which results in a learning curve for providers. Some healthcare workers, especially those who did not grow up with technology, may not be adept at using EHRs.

“Missing health information can sometimes be as simple as a person who isn’t sure what button to push in the new system,” Gurupur says.

Ayan Nasir ’20MD is finishing his internal medicine residency at Mayo Clinic in Jacksonville, Florida. As a UCF undergraduate and medical student, Nasir did research with Gurupur on health informatics. Before entering the medical field, Nasir worked in finance and says he was amazed at the quality control and data accuracy differences difference between banking and health records. Those discrepancies inspired him to make improving health informatics the subject of his two-year Focused Inquiry and Research Experience (FIRE) project at the medical school, where Gurupur served as his research mentor.

His residency has reinforced his passion for improving health informatics.

“When I see a patient, what I put in the electronic health record reflects one episode of their care,” he says. “But that information is going to guide every future medical decision. That’s why electronic records must be complete.”

Gurupur gave this example to highlight the impact of incomplete health data. A patient with limited English skills visits a new provider who does not speak the patient’s native language. With their communication challenges and the rush of a clinical practice, the patient forgets to mention that they are on a particular drug for Type 2 diabetes. There is nothing about previous diabetes treatment in the electronic health record so the provider prescribes a standard drug in a standard dosage for that condition. Now the patient can be receiving twice the recommended amount.

Medicine is looking at ways to use more big data — artificial intelligence — to diagnose and provide more evidence-based treatments. But that computer analysis relies on complete patient data, Nasir points out.

“When it comes to medicine, you’re only as good as your data,” he says.

Gurupur says developing reliable algorithms for missing data is also important to health systems. Recent studies have shown that hospitals can lose an average of $5 to $8 million a year because of missing data that impacts their insurance reimbursement rates. With the algorithm, hospital leaders can learn exactly where missing information is coming from — a particular floor, department, service — and address it.

Both Gurupur and Nasir believe health informatics is at a critical tipping point. Health systems rely on electronic records but must develop ways to ensure all the information they collect is complete and accurate. Nasir is getting his master’s in health informatics at Northwestern University and points out that such graduate medical training programs show the increasing importance of using data to better care for patients. He believes future health technology will improve care even more — computers will translate conversations between providers and patients directly into the electronic record, reducing the need for providers to input data manually after each visit, for example.

“We are just at the beginning of this transformation,” he says. “It’s exciting to be part of this work.”

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Materials provided by University of Central Florida. Original written by Wendy Sarubbi. Note: Content may be edited for style and length.

In work published in Nature Communications, the researchers made multiple 3-by-3 grids of precisely spaced quantum dots, each comprising one to three phosphorus atoms. Attached to the grids were electrical leads and other components that enabled electrons to flow through them. The grids provided playing fields in which electrons could behave in nearly ideal, textbook-like conditions, free of the confounding effects of real-world materials.

The researchers injected electrons into the grids and observed how they behaved as the researchers varied conditions such as the spacing between the dots. For grids in which the dots were close, the electrons tended to spread out and act like waves, essentially existing in several places at one time. When the dots were far apart, they would sometimes get trapped in individual dots, like electrons in materials with insulating properties.

Advanced versions of the grid would allow researchers to study the behavior of electrons in controllable environments with a level of detail that would be impossible for the world’s most powerful conventional computers to simulate accurately. It would open the door to full-fledged “analog quantum simulators” that unlock the secrets of exotic materials such as high-temperature superconductors. It could also provide hints about how to create materials, such as topological insulators, by controlling the geometry of the quantum dot array.

In related work just published in ACS Nano, the same NIST researchers improved their fabrication method so they can now reliably create an array of identical, equally spaced dots with exactly one atom each, leading to even more ideal environments necessary for a fully accurate quantum simulator. The researchers have set their sights on making such a simulator with a larger grid of quantum dots: A 5×5 array of dots can produce rich electron behavior that is impossible to simulate in even the most advanced supercomputers.

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Materials provided by National Institute of Standards and Technology (NIST). Note: Content may be edited for style and length.