Sensitive new test detects antibodies against SARS-CoV-2 in only 10 minutes

As the COVID-19 curve shows signs of flattening in the U.S. and elsewhere, public health officials are trying to grasp just how many people have been infected. Now, a proof-of-concept study in ACS’ Analytical Chemistry describes a quick, sensitive test for antibodies against the coronavirus in human blood. The test could help doctors track a person’s exposure to the disease, as well as confirm suspected COVID-19 cases that tested negative by other methods.

Because COVID-19 symptoms range from mild to severe, with some people apparently having no symptoms, the number of people who have been infected with the SARS-CoV-2 virus at some point is likely much higher than the number of confirmed cases. As U.S. states begin to ease lockdown restrictions, widespread testing of the general population will be important to identify people at early stages of disease, or people who lack symptoms but can still infect others. Also, although more research needs to be done, it is possible that people with antibodies to the virus could be immune to future COVID-19 outbreaks. To help identify people with current or past exposure to SARS-CoV-2, Lei Yu, Yingsong Wu, Guanfeng Lin and colleagues wanted to develop a fast, sensitive antibody test.

The researchers based their test on a technique called a lateral flow immunoassay (LFA); a home pregnancy test is an example of this kind of assay. They attached a viral coat protein to a specific region on a strip of nitrocellulose, and then added human serum. The serum flowed from one end of the strip to the other, and any antibodies against the viral protein bound to that region on the strip. Then, the team detected the anti-SARS-CoV-2 antibodies with a fluorescently labeled antibody. This fluorescence-based detection is much more sensitive than some other LFAs, such as pregnancy tests, that can be read by the naked eye. The researchers tested the new assay on seven serum samples from COVID-19 patients and 12 samples from people who had tested negative for the disease by reverse transcriptase-polymerase chain reaction (RT-PCR), a common diagnostic test that occasionally fails to detect positive cases. The new assay correctly diagnosed all seven samples as positive — as well as an additional “negative” case that had suspicious clinical symptoms — in only 10 minutes per sample. The immunoassay could be helpful in confirming negative diagnoses, monitoring a patient’s recovery, studying past exposures, and identifying recovered individuals with high levels of antibodies as potential convalescent plasma donors, the researchers say.

The authors acknowledge funding from the National Natural Science Foundation of China and the China Postdoctoral Science Foundation.

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Materials provided by American Chemical Society. Note: Content may be edited for style and length.

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Scientists see energy gap modulations in a cuprate superconductor

For years physicists have been trying to decipher the electronic details of high-temperature superconductors. These materials could revolutionize energy transmission and electronics because of their ability to carry electric current with no energy loss when cooled below a certain temperature. Details of “high-Tc” superconductors’ microscopic electronic structure could reveal how different phases (states of matter) compete or interact with superconductivity — a state in which like-charged electrons somehow overcome their repulsion to pair up and flow freely. The ultimate goal is to understand how to make these materials act as superconductors without the need for supercooling.

Now scientists studying high-Tc superconductors at the U.S. Department of Energy’s Brookhaven National Laboratory have definitive evidence for the existence of a state of matter known as a pair density wave — first predicted by theorists some 50 years ago. Their results, published in the journal Nature, show that this phase coexists with superconductivity in a well-known bismuth-based copper-oxide superconductor.

“This is the first direct spectroscopic evidence that the pair density wave exists at zero magnetic field,” said Kazuhiro Fujita, the physicist who led the research at Brookhaven Lab. “We’ve identified that the pair density wave plays an important role in this material. Our results show that these two states of matter — pair density wave and superconductivity — coexist and interact.”

The team’s results come from measurements of single electrons’ tunneling spectra using a state-of-the-art spectroscopic-imaging scanning tunneling microscope (SI-STM) in Brookhaven’s OASIS laboratory.

“What we measure is how many electrons at a given location ‘tunnel’ from the sample surface to the superconducting electrode tip of the SI-STM and vice versa as we vary the energy (voltage) between the sample and the tip,” Fujita said. “With those measurements we can map out the crystalline lattice and the electron density of states — as well as the number of electrons we have at a given location.”

When the material is not superconducting, electrons exist over a continuous spectrum of energies, each propagating at its own unique wavelength. But when the temperature goes down, the electrons start to interact — pairing up as the material enters the superconducting state. When this happens, scientists observe a gap in the energy spectrum, created by an absence of electrons within that particular energy range.

“The energy of the gap is equal to the energy it takes to break the electron pairs apart (which tells you how tightly bound they were),” Fujita said.

As the scientists scanned across the surface of the material, they detected spatially modulating energy gap structures. These modulations in the energy gap revealed that the strength of electrons’ binding varies — increasing to a maximum, then dipping to a minimum — with this pattern repeating every eight atoms across the surface of the regularly arrayed crystal lattice.

This work built on previous measurements showing that the current created by pairs of electrons tunneling into the microscope also varied in the same periodic way. Those modulations in current were the first evidence, though somewhat circumstantial, that the pair density wave was present.

“Modulations in the current of the paired electrons is an indicator that there are modulations in how strongly paired the electrons are across the surface. But this time, by measuring the energy spectrum of individual electrons, we succeeded in directly measuring the modulating gap in the spectra where pairing occurs. The modulations in the size of those gaps is direct spectroscopic evidence that the pair density wave state exists,” Fujita said.

The new results also included evidence of other key signatures of the pair density wave — including defects called “half-vortices” — as well as its interactions with the superconducting phase.

In addition, the energy gap modulations mirror other Brookhaven Lab research indicating the existence of modulating patterns of electronic and magnetic characteristics — sometimes referred to as “stripes” — that also occur with an eight-unit-cell periodicity in certain high-Tc cuprate superconductors.

“Together these findings indicate that the pair density wave plays a significant role in these materials’ superconducting properties. Understanding this state may help us make sense of the complex phase diagram that maps out how superconducting properties emerge under different conditions, including temperature, magnetic field, and charge-carrier density,” Fujita said.

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IEEE Spectrum

CES 2020: Bzigo Laser System Detects and Tracks Mosquitoes So You Can Destroy Them

As far as I know, the current state of the art in indoor mosquito management is frantically trying to determine where that buzzing noise is coming from so that you can whack the damn bug before it lands and you lose track of it.

This “system” rarely works, but at CES this week, we found something better: Israeli startup Bzigo (the name of both the company and the product), which makes a mosquito detection and tracking system that combines an IR camera and laser designator with computer vision algorithms that follows mosquitoes as they fly and tells you exactly where they land to help you smash them. It’s not quite as deadly as the backyard star wars system, but it’s a lot more practical, because you’ll be able to buy one.

Bzigo’s visual tracking system can reliably spot mosquitoes at distances of up to 8 meters. A single near-IR (850nm) camera with a pair of IR illuminators and a wide angle lens can spot mosquitoes over an entire room, day or night. Once a bug is detected, an eye-safe laser will follow it until it lands and then draws a box around it for you so you can attack with your implement of choice.

At maximum range, you run into plenty of situations where the apparent size of a mosquito can be less than a single pixel. Bzigo’s AI relies on a mosquito’s motion rather than an identifiable image of the bug itself, and tracking those potentially intermittent and far-off pixel traces requires four 1GHz cores running at 100% continuously (all on-device). That’s a lot of oomph, but the result is that false positives are down around 1%, and 90% of landings are detected. This is not to say that the system can only detect 90% of bugs— since mosquitoes take off and land frequently, they’re almost always detected after just a few flight cycles. It’s taken Bzigo four years to reach this level of accuracy and precision with detection and tracking, and it’s impressive.

The super obvious missing feature is that this system only points at mosquitoes, as opposed to actually dealing with them in a direct (and lethal) way. You could argue that it’s the detection and tracking that’s the hard part (and it certainly is for humans), and that automated bug destruction is a lower priority, and you’d probably be right.

Or at least, Bzigo would agree with you, because that’s the approach they’ve taken. However, there are plans for a Bzigo V2, which adds a dedicated mosquito killing feature. If you guessed that said feature would involve replacing the laser designator with a much higher powered laser bug zapper, you’d be wrong, because we’re told that the V2 will rely on a custom nano-drone to destroy its winged foes at close range.

Bzigo has raised one round of funding, and they’re currently looking to raise a bit more to fund manufacturing of the device. Once that comes through, the first version of the system should be available in 12-14 months for about $170.


How universities may help bridge social divide between international, domestic students

Self-esteem is a valuable resource for undergraduate international students trying to socialize with their domestic counterparts at American universities, but new research by a University at Buffalo psychologist suggests that while self-esteem predicts better socialization with domestic students, it is curiously unrelated to how international students socialize with other internationals.

“Self-esteem affords confidence,” says Wendy Quinton, a clinical associate professor of psychology in UB’s College of Arts and Sciences. “So people higher in self-esteem have more belief in themselves and their abilities, and that is particularly helpful when trying to initiate contact with people from the host culture.”

Understanding that self-esteem — someone’s feelings of self-worth and personal value — contributes to socialization with one group and not the other is among the factors distinguishing Quinton’s study, recently published in the International Journal of Intercultural Relations.

“These results underscore the importance of examining individual differences to better understand how international students adapt to their new learning environment,” says Quinton, PhD, an expert in the international student experience. “The findings also indicate that self-esteem may be viewed as a coping resource for international students when they interact with domestic students.”

In addition to self-esteem, Quinton also examined university identity and perceived discrimination in the current study.

University identity, the degree to which students feel connected with their university community, was associated with greater socialization with both groups, although not as strongly as self-esteem. Perceived discrimination, the feeling that you or a group you belong to is the target of prejudice, was unrelated to socialization.

Previous research in this area hasn’t looked at these predictors of socialization together, nor has it explored the interesting divergence between the two student groups, a method that enabled Quinton to statistically control for socialization with one group in order to investigate the other.

“This approach allowed for a specific test of what predicts socialization with each student group, above and beyond an individual’s general level of sociability,” she says.

International students often prioritize interacting with host nationals as an important part of their experience while studying in the U.S. But for the vast majority of international students, that aspiration is a challenging and often unfulfilled goal, hampered by structural barriers that range from cultural adaptation to navigating the trials of higher education.

But socialization has benefits beyond human interaction. It’s associated with less depression, lower levels of homesickness, better stress management, and greater life satisfaction. It is not friendship, but rather an entry-level interaction between people with the potential to become friendship, which Quinton measured as time spent doing joint recreational activities, with whom people are studying and with whom they choose to spend their free time.

Quinton’s study focused on East and Southeast Asian students, the largest international demographic attending American universities.

“This group also has some of the largest cultural divides to bridge when coming to the U.S.,” says Quinton. “The independence emphasized in Western culture is often at odds with the emphasis on cooperation and interdependence in collectivistic cultures like China, South Korea and many Southeast Asian countries. That’s a very different orientation to what these students are accustomed to in their home culture.”

But it’s something universities can address, according to Quinton. Anything that fosters a connection and sense of a shared experience between international and domestic students, both the stress and anxieties, as well as the joys and pleasures, is going to be a “win-win.” Quinton also highlighted low self-esteem as “a potential risk factor for international students, one that universities might look for in terms of identifying students who are potentially vulnerable for missing out.”

“International students who fall short of the expected connection with U.S. students are clearly disappointed, but there’s also a loss for the domestic student population, entering a global community, who are deprived of the benefits associated with interacting with people from varied and different backgrounds.

“Domestic students, in this case, are undoubtedly losing out, by not getting to know international students,” says Quinton.

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Building a better battery with machine learning

Designing the best molecular building blocks for battery components is like trying to create a recipe for a new kind of cake, when you have billions of potential ingredients. The challenge involves determining which ingredients work best together — or, more simply, produce an edible (or, in the case of batteries, a safe) product. But even with state-of-the-art supercomputers, scientists cannot precisely model the chemical characteristics of every molecule that could prove to be the basis of a next-generation battery material.

Instead, researchers at the U.S. Department of Energy’s (DOE) Argonne National Laboratory have turned to the power of machine learning and artificial intelligence to dramatically accelerate the process of battery discovery.

As described in two new papers, Argonne researchers first created a highly accurate database of roughly 133,000 small organic molecules that could form the basis of battery electrolytes. To do so, they used a computationally intensive model called G4MP2. This collection of molecules, however, represented only a small subset of 166 billion larger molecules that scientists wanted to probe for electrolyte candidates.

Because using G4MP2 to resolve each of the 166 billion molecules would have required an impossible amount of computing time and power, the research team used a machine learning algorithm to relate the precisely known structures from the smaller data set to much more coarsely modeled structures from the larger data set.

“When it comes to determining how these molecules work, there are big tradeoffs between accuracy and the time it takes to compute a result,” said Ian Foster, Argonne Data Science and Learning division director and author of one of the papers. “We believe that machine learning represents a way to get a molecular picture that is nearly as precise at a fraction of the computational cost.”

To provide a basis for the machine learning model, Foster and his colleagues used a less computationally taxing modeling framework based on density functional theory, a quantum mechanical modeling framework used to calculate electronic structure in large systems. Density functional theory provides a good approximation of molecular properties, but is less accurate than G4MP2.

Refining the algorithm to better ascertain information about the broader class of organic molecules involved comparing the atomic positions of the molecules computed with the highly accurate G4MP2 versus those analyzed using only density functional theory. By using G4MP2 as a gold standard, the researchers could train the density functional theory model to incorporate a correction factor, improving its accuracy while keeping computational costs down.

“The machine learning algorithm gives us a way to look at the relationship between the atoms in a large molecule and their neighbors, to see how they bond and interact, and look for similarities between those molecules and others we know quite well,” said Argonne computational scientist Logan Ward, an author of one of the studies. “This will help us to make predictions about the energies of these larger molecules or the differences between the low- and high-accuracy calculations.”

“This whole project is designed to give us the biggest picture possible of battery electrolyte candidates,” added Argonne chemist Rajeev Assary, an author of both studies. “If we are going to use a molecule for energy storage applications, we need to know properties like its stability, and we can use this machine learning to predict properties of bigger molecules more accurately.”

A paper describing the formation of the G4MP2-based dataset, “Accurate quantum chemical energies for 133,000 organic molecules,” appeared in the June 27 online issue of Chemical Science.

A second paper describing the machine learning algorithm, “Machine learning prediction of accurate atomization energies of organic molecules from low-fidelity quantum chemical calculations,” appeared in the August 27 issue of MRS Communications.

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Materials provided by DOE/Argonne National Laboratory. Original written by Jared Sagoff. Note: Content may be edited for style and length.

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Tired of Opening Your Own Curtains? Use an ESP32 to Do It Automatically

It’s an sad scene: your alarm clock starts blaring at 7am. You’re groggy and trying to rub the final remnants of a dream from your eyes. You know you need to climb out of bed soon in order to have the time to drink some coffee and still get to work by 9:10. But your darkened room is tricking your semi-conscious brain into believing it’s still nighttime. Opening the curtains to let some light in would certainly help, but you’re not some kind of peasant who has to open curtains yourself. The solution, as redditor nutstobutts has proven, is to use an ESP32 to open the curtains for you — like royalty does.

Dramatic infomercial-style reenactments aside, this setup would be quite handy if you like some sunlight in the mornings. You could either program it to open, and then close, the curtains at specific times of day, or you could integrate it into your smart home or IoT (Internet of Things) system. nutstobutts doesn’t provide a lot of detail about how his curtains are programmed, but this would be fairly easy to replicate yourself if you’re interested.

The curtains themselves are hanging from a rod of extruded aluminum. Two sliding carriages also ride on that aluminum extrusion. There are two stepper motors, one mounted on each side of the curtain rod, which pull the carriage either left or right via a belt and pulley. Those are controlled by an ESP32 board through a stepper motor driver. The use of two motors allows the curtain to be opened symmetrically, but one motor is sufficient if you want your curtains to open to one side. The ESP32 has both WiFi and Bluetooth built-in, so you have options on how to send the “open” and “close” commands. If you’re tired of opening your own curtains, this is definitely a project worth tackling.

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Author: Cameron Coward


How diabetes can increase cancer risk: DNA damaged by high blood sugar

For years, scientists have been trying to solve a medical mystery: Why do people with type 1 or type 2 diabetes have an increased risk of developing some forms of cancer? Today, researchers report a possible explanation for this double whammy. They found that DNA sustains more damage and gets fixed less often when blood sugar levels are high compared to when blood sugar is at a normal, healthy level, thereby increasing one’s cancer risk.

The researchers will present their results at the American Chemical Society (ACS) Fall 2019 National Meeting & Exposition.

“It’s been known for a long time that people with diabetes have as much as a 2.5-fold increased risk for certain cancers,” says John Termini, Ph.D., who is presenting the work at the meeting. These cancers include ovarian, breast, kidney and others. “As the incidence of diabetes continues to rise, the cancer rate will likely increase, as well.”

Scientists have suspected that the elevated cancer risk for diabetics arises from hormonal dysregulation. “In people with type 2 diabetes, their insulin is not effectively carrying glucose into cells,” Termini explains. “So the pancreas makes more and more insulin, and they get what’s called hyperinsulinemia.” In addition to controlling blood glucose levels, the hormone insulin can stimulate cell growth, possibly leading to cancer. Also, most people with type 2 diabetes are overweight, and their excess fat tissue produces higher levels of adipokines than those at a healthy weight. These hormones promote chronic inflammation, which is linked to cancer. “The most common idea is that the increased cancer risk has to do with hormones,” Termini says. “That’s probably part of it, but there hasn’t been a lot of solid evidence.”

Termini, who is at City of Hope, a research and treatment center for cancer and diabetes, had a different idea. He wondered if the elevated blood glucose levels seen in diabetes could harm DNA, making the genome unstable, which could lead to cancer. So Termini and colleagues looked for a specific type of damage in the form of chemically modified DNA bases, known as adducts, in tissue culture and rodent models of diabetes. Indeed, they found a DNA adduct, called N2-(1-carboxyethyl)-2′-deoxyguanosine, or CEdG, that occurred more frequently in the diabetic models than in normal cells or mice. What’s more, high glucose levels interfered with the cells’ process for fixing it. “Exposure to high glucose levels leads to both DNA adducts and the suppression of their repair, which in combination could cause genome instability and cancer,” Termini says.

Recently, Termini and colleagues completed a clinical study that measured the levels of CEdG, as well as its counterpart in RNA (CEG), in people with type 2 diabetes. As in mice, people with diabetes had significantly higher levels of both CEdG and CEG than people without the disease.

But the team didn’t stop there. They wanted to determine the molecular reasons why the adducts weren’t being fixed properly by the cells. They identified two proteins that appear to be involved: the transcription factor HIF1α and the signaling protein mTORC1, which both show less activity in diabetes. HIF1α activates several genes involved in the repair process. “We found that if we stabilize HIF1α in a high-glucose environment, we increase DNA repair and reduce DNA damage,” Termini says. “And mTORC1 actually controls HIF1α, so if you stimulate mTORC1, you stimulate HIF1α.”

According to Termini, several drugs that stimulate HIF1α or mTORC1 already exist. The researchers plan to see if these drugs decrease cancer risk in diabetic animal models, and if so, they will test them in humans. Termini notes that metformin, a common diabetes medication that helps lower blood glucose levels, also stimulates DNA repair. “We’re looking at testing metformin in combination with drugs that specifically stabilize HIF1α or enhance mTORC1 signaling in diabetic animal models,” he says. In the meantime, a more immediate way for diabetics to reduce their cancer risk could be better control of their blood sugar. “That sounds like such an easy solution, but it’s extremely difficult for most people to maintain glycemic control,” Termini says.

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Materials provided by American Chemical Society. Note: Content may be edited for style and length.

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An Automatic Kite String Winder

Flying a kite can be fun, but what’s not fun is trying to wrap hundreds of feed of string onto a spool when you’re done. In order to avoid this annoyance, Matt Bilsky designed his own “Automatic Kite String Reeler-Inner” to do it for him. The design is something of a remake of a device he made when he was 8 years old. While that one never really worked as he’d hoped, with new engineering and design techniques learned in the next 20 or so years, he’s revisited the project, making something that appears to works quite well.

His new build consists of mostly 3D-printed parts, and uses a motor from a standard portable power drill to reel in the string. This gives it enough torque and speed for the job, and allows him to use off-the-shelf rechargeable batteries for power. He even embedded a pair of USB ports, as well as a 12VDC socket in the rig, enabling it to also charge phones or even as a power source to blow up inflatable beach toys as needed.

Mechanically, the project is quite clever, and features a rotary cam system to pull the string back and forth in order to balance how its winding. He even made the device in such a way that the spool can be used independently and placed in the winder when needed — potentially useful when flying multiple kites. The device is demonstrated in the first video below, and more info on the design and build process is seen in the second.

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Author: Jeremy S. Cook