Category: Science

In an intensive look at the effects of the virus causing COVID-19 on patients’ microbiome, researchers found that acute infection disrupts a healthy balance between good and bad microbes in the gut, especially with antibiotic treatment.

The microbiome is the collection of microorganisms that live in and on the human body.

The new work may lead to the development of probiotic supplements to redress any gut imbalances in future patients, the researchers say.

Reporting in the scientific journal Molecular Biomedicine, the researchers described the first results of an ongoing study examining the microbiome of patients and volunteers at Robert Wood Johnson University Hospital in New Brunswick.

“These findings may help identify microbial targets and probiotic supplements for improving COVID-19 treatment.”

The study, which began in May 2020, the early days of the pandemic, was designed to zero in on the microbiome because many COVID-19 patients complained of gastrointestinal issues—both during the acute phases of their illness and while recuperating.

“We wanted to gain a deeper understanding by looking at specimens that would give us an indication about the state of the gut microbiome in people,” says Martin Blaser, chair of the human microbiome at Rutgers University, director of the Center for Advanced Biotechnology and Medicine (CABM) at Rutgers, and an author on the study.

“What we found was that, while there were differences between people who had COVID-19 and those who were not ill, the biggest difference from others was seen in those who had been administered antibiotics,” Blaser says.

Early in the pandemic, before the introduction of vaccines and other antiviral remedies, it was a common practice to treat COVID-19 patients with a round of antibiotics to attempt to target possible secondary infections, says Blaser, who also is a professor of medicine and pathology and laboratory medicine at Rutgers Robert Wood Johnson Medical School.

Humans carry large and diverse populations of microbes, Blaser says. These microorganisms live in the gastrointestinal tract, on the skin and in other organs, with the largest population in the colon. Scientists such as Blaser have shown over recent decades that the microbiome plays a pivotal role in human health, interacting with metabolism, the immune system and the central nervous system.

The microbiome has many different functions. “One is to protect the human body against invading pathogens, whether they’re bacteria or viruses or fungi,” Blaser says. “That goes deep into evolution, maybe a billion years of evolution.”

Medical problems often arise when the balance between beneficial and pathogenic microbes in a person’s microbiome is thrown off, a condition known as dysbiosis.

The scientists studied microbiomes by measuring populations of microorganisms in stool samples taken from 60 subjects. The study group consisted of 20 COVID-19 patients, 20 healthy donors, and 20 COVID-19-recovered subjects. They found major differences in the population numbers of 55 different species of bacteria when comparing the microbiomes of infected patients with the healthy and recovered patients.

The researchers plan to continue to test and track the microbiomes of patients in the study to ascertain the long-term effect on individual microbiomes from COVID-19.

“Further investigation of patients will enhance understanding of the role of the gut microbiome in COVID-19 disease progression and recovery,” Blaser says. “These findings may help identify microbial targets and probiotic supplements for improving COVID-19 treatment.”

Support for the study came from Danone and by the National Institutes of Health (National Institute of Allergy and Infectious Diseases).

Source: Rutgers University

New findings are a step towards understanding why some people gain more weight than others, even when they eat the same diet.

The research indicates that some Danish people have a composition of gut microbes that, on average, extracts more energy from food than do the microbes in the guts of their fellow Danes. Part of the explanation could be related to the composition of their gut microbes.

Researchers at the University of Copenhagen’s department of nutrition, exercise, and sports studied the residual energy in the feces of 85 Danes to estimate how effective their gut microbes are at extracting energy from food. At the same time, they mapped the composition of gut microbes for each participant.

The results show that roughly 40% of the participants belong to a group that, on average, extracts more energy from food compared to the other 60%. The researchers also observed that those who extracted the most energy from food also weighed 10% more on average, amounting to an extra nine kilograms (about 20 pounds).

“We may have found a key to understanding why some people gain more weight than others, even when they don’t eat more or any differently. But this needs to be investigated further,” says associate professor Henrik Roager.

The results indicate that being overweight might not be related to how healthily a person eats or the amount of exercise they get. It may also have something to do with the composition of their gut microbes.

As reported in the journal Microbiome, participants were divided into three groups, based on the composition of their gut microbes. The so-called B-type composition (dominated by Bacteroides bacteria) is more effective at extracting nutrients from food and was observed in 40% of the participants.

Following the study, the researchers suspect that having gut bacteria that are more effective at extracting energy may result in more calories being available for the human host from the same amount of food.

“The fact that our gut bacteria are great at extracting energy from food is basically a good thing, as the bacteria’s metabolism of food provides extra energy in the form of, for example, short-chain fatty acids, which are molecules that our body can use as energy-supplying fuel. But if we consume more than we burn, the extra energy provided by the intestinal bacteria may increase the risk of obesity over time,” says Roager.

From mouth to esophagus, stomach, duodenum, and small intestine, large intestine, and finally to rectum, the food we eat takes a 12-to-36-hour journey, passing several stations along the way, before the body has extracted all the food’s nutrients.

The researchers also studied the length of this journey for each participant, all of whom had similar dietary patterns. Here, the researchers hypothesized that those with long digestive travel times would be the ones who harvested the most nutrition from their food. But the study found the exact opposite.

“We thought that there would be a long digestive travel time would allow more energy to be extracted. But here, we see that participants with the B-type gut bacteria that extract the most energy, also have the fastest passage through the gastrointestinal system, which has given us something to think about,” says Roager.

The new study in humans confirms earlier studies in mice. In these studies, researchers found that germ-free mice that received gut microbes from obese donors gained more weight compared to mice that received gut microbes from lean donors, despite being fed the same diet.

Even then, the researchers proposed that the differences in weight gain could be attributable to the fact that the gut bacteria from obese people were more efficient at extracting energy from food. The new research confirms this theory.

“It is very interesting that the group of people who have less energy left in their stool also weigh more on average. However, this study doesn’t provide proof that the two factors are directly related. We hope to explore this more in the future,” says Roager.

Source: University of Copenhagen

A new study shows how machine learning could predict rare disastrous events, like earthquakes or pandemics.

The research suggests how scientists can circumvent the need for massive data sets to forecast extreme events with the combination of an advanced machine learning system and sequential sampling techniques.

When it comes to predicting disasters brought on by extreme events (think earthquakes, pandemics, or “rogue waves” that could destroy coastal structures), computational modeling faces an almost insurmountable challenge: Statistically speaking, these events are so rare that there’s just not enough data on them to use predictive models to accurately forecast when they’ll happen next.

But the new research indicates it doesn’t have to be that way.

In the study in Nature Computational Science, the researchers describe how they combined statistical algorithms—which need less data to make accurate, efficient predictions—with a powerful machine learning technique and trained it to predict scenarios, probabilities, and sometimes even the timeline of rare events despite the lack of historical record on them.

Doing so, the researchers found that this new framework can provide a way to circumvent the need for massive amounts of data that are traditionally needed for these kinds of computations, instead essentially boiling down the grand challenge of predicting rare events to a matter of quality over quantity.

“You have to realize that these are stochastic events,” says study author George Karniadakis, a professor of applied mathematics and engineering at Brown University. “An outburst of pandemic like COVID-19, environmental disaster in the Gulf of Mexico, an earthquake, huge wildfires in California, a 30-meter wave that capsizes a ship—these are rare events and because they are rare, we don’t have a lot of historical data.

“We don’t have enough samples from the past to predict them further into the future. The question that we tackle in the paper is: What is the best possible data that we can use to minimize the number of data points we need?”

The researchers found the answer in a sequential sampling technique called active learning. These types of statistical algorithms are not only able to analyze data input into them, but more importantly, they can learn from the information to label new relevant data points that are equally or even more important to the outcome that’s being calculated. At the most basic level, they allow more to be done with less.

That’s critical to the machine learning model the researchers used in the study. Called DeepOnet, the model is a type of artificial neural network, which uses interconnected nodes in successive layers that roughly mimic the connections made by neurons in the human brain.

DeepOnet is known as a deep neural operator. It’s more advanced and powerful than typical artificial neural networks because it’s actually two neural networks in one, processing data in two parallel networks. This allows it to analyze giant sets of data and scenarios at breakneck speed to spit out equally massive sets of probabilities once it learns what it’s looking for.

The bottleneck with this powerful tool, especially as it relates to rare events, is that deep neural operators need tons of data to be trained to make calculations that are effective and accurate.

In the paper, the research team shows that combined with active learning techniques, the DeepOnet model can get trained on what parameters or precursors to look for that lead up to the disastrous event someone is analyzing, even when there are not many data points.

“The thrust is not to take every possible data and put it into the system, but to proactively look for events that will signify the rare events,” Karniadakis says. “We may not have many examples of the real event, but we may have those precursors. Through mathematics, we identify them, which together with real events will help us to train this data-hungry operator.”

In the paper, the researchers apply the approach to pinpointing parameters and different ranges of probabilities for dangerous spikes during a pandemic, finding and predicting rogue waves, and estimating when a ship will crack in half due to stress. For example, with rogue waves—ones that are greater than twice the size of surrounding waves—the researchers found they could discover and quantify when rogue waves will form by looking at probable wave conditions that nonlinearly interact over time, leading to waves sometimes three times their original size.

The researchers found their new method outperformed more traditional modeling efforts, and they believe it presents a framework that can efficiently discover and predict all kinds of rare events.

In the paper, the research team outlines how scientists should design future experiments so that they can minimize costs and increase the forecasting accuracy. Karniadakis, for example, is already working with environmental scientists to use the novel method to forecast climate events, such as hurricanes.

Ethan Pickering and Themistoklis Sapsis from the Massachusetts Institute of Technology led the study. Karniadakis and other Brown researchers introduced DeepOnet in 2019. They are currently seeking a patent for the technology.

Support for the study came from the Defense Advanced Research Projects Agency, the Air Force Research Laboratory, and the Office of Naval Research.

Source: Juan Siliezar for Brown University

WASHINGTON — After a record-setting year of launch activity in 2022, SpaceX kicked off the new year Jan. 3 with a Falcon 9 launch of more than 110 smallsats.

The Falcon 9 lifted off on the Transporter-6 dedicated smallsat rideshare mission at 9:56 a.m. Eastern from Cape Canaveral’s Space Launch Complex 40. The rocket’s first stage, making its 15th flight, landed back at the Cape’s Landing Zone 1 eight and a half minutes after liftoff.

The rocket’s upper stage started releasing its 114 payloads into sun-synchronous orbit nearly an hour after liftoff, a process involving 82 individual deployments that took more than a half-hour to complete. SpaceX was able to confirm 77 of the deployments in real time.

The largest single customer on the launch, in terms of number of satellites, was Planet, which had 36 of its SuperDove imaging satellites on board. Planet has now launched more than 500 satellites, mostly cubesats like the SuperDoves.

Some of the other major payloads on Transporter-6 included:

• Six LEMUR cubesats for Spire, which operates a constellation for collecting weather and tracking data;
• Four imaging satellites for Satellogic, which has slowed the deployment of its constellation after revenues fell short of projections in 2022;
• Four radio-frequency intelligence satellites for Luxembourg-based Kleos and the BRO-8 radio-frequency intelligence satellite for French startup Unseenlabs;
• Three synthetic aperture radar (SAR) imaging satellites for Iceye and two SAR satellites for Umbra;
• Two satellites for Lynk, which is developing a constellation to provide direct-to-handset connectivity services;
• Twelve SpaceBee internet-of-things satellites for SpaceX-owned Swarm Technologies;
• Gama Alpha, the first satellite by French company Gama to test solar sail technologies;
• The Electro-Optical/Infrared Weather Systems (EWS) technology demonstration cubesat for the U.S. Space Force’s Space Systems Command

Several of the payloads on Transporter-6 are orbital transfer vehicles that will later deploy satellites. They include two ION vehicles from D-Orbit, the second Vigoride tug from Momentus and Launcher’s first Orbiter vehicle.

Transporter-6 is the sixth in a series of smallsat rideshare missions by SpaceX, which performed the first two Transporter missions in 2021 and three in 2022. The company said in August that it continues to see strong demand for the services despite the rise in small launch vehicles that offer dedicated launch options for smallsats. All of SpaceX’s Transporter missions for 2023 are full, the company said then, although last-minute opportunities may arise.

A record 2022

Transporter-6 was the first orbital launch globally in 2023. It comes after a record 2022, when there were 186 orbital launch attempts, 40 more than 2021. A total of 179 launches were successful, compared to 136 in 2021.

Orbital launch activity has doubled in just the last five years. In 2017 there were 86 successful orbital launches in 90 attempts. SpaceX is responsible for much of that growth, having gone from 18 launches in 2017 to 61 in 2022, while Chinese launches increased from 18 in 2017 to 64 in 2022.

With the exception of New Zealand, which went from the first Rocket Lab Electron launch in 2017 to nine in 2022, other countries saw flat or reduced launch activity over the last five years. That includes Europe, which went from 11 launches in 2017 to 6 in 2022, and Japan, which had seven launches in 2017 but only a single, unsuccessful Epsilon launch in 2022.

SpaceX, whose 61 launches in 2022 were nearly double the 31 launches it conducted in 2021, will attempt to set another launch record in 2023. SpaceX founder Elon Musk has suggested the company will attempt as many as 100 launches in 2023, a total that likely include its Starship vehicle, whose first orbital launch is expected some time this year.

People who don’t habitually turn off their automatic sprinklers are wasting water, say researchers.

In Florida, with a population of 22 million, a figure projected to hit 27.8 million by 2050, residents need to conserve the precious resource.

Preserving water boils down to good habits. It can be as simple as whether you intend to save water or not, say researchers, who would like to change the behavior of those who leave their sprinklers on when it’s raining.

“A lot of people do not think about how rain plays into the total amount of water a yard receives,” says Laura Warner, an associate professor of agricultural education and communication at the University of Florida Institute of Food and Agricultural Sciences (UF/IFAS).

“So, if someone wants to apply a half-inch of water to their lawn, they may set their irrigation system to do so regularly, and then if it rains, that is just ‘extra.’ It would be advantageous to shift people’s mindsets, so they consider rain first and irrigation supplemental.”

Warner and John Diaz, associate professor of agricultural education and communication, are coauthors of a new study that examines whether homeowners intend to turn off their irrigation when it rains—the so-called “intenders.”

The researchers conducted an online survey of 331 Florida residents who identified themselves as users of automated sprinkler systems.

They wanted to know whether homeowners intended to turn off their water, based on recent or current rain.

To find their answer, researchers asked questions such as, “How likely are you to use local weather data to turn off your irrigation when recent rainfall is adequate for your yard in the next month?” Respondents could select from “very unlikely” to “very likely” for all three questions.

Researchers labeled respondents with the highest score as “intenders.” In other words, the person plans to turn off the irrigation system when it’s raining. They also intend to turn off their water if it’s rained a lot recently and see no reason to water their lawn.

Warner and Diaz want to change the habits of “non-intenders.”

“Rather than just providing information on how to conserve water or why—which is not terribly effective—we want to connect with people and have them connect with water resources on a deeper psychological level,” Warner says. In other words, homeowners must feel a sense of obligation to conserve water.

To move toward wiser lawn-irrigation habits, UF/IFAS Extension agents, governments, homeowners’ associations, and neighbors can nudge residents to stop or reduce irrigating when it’s raining. One way to do that is by pointing out that other homeowners are turning off their sprinklers, Warner says.

Sometimes, reminders such as signs at the entrance to a subdivision help. They tell residents how much rain fell the week before and ask residents if they need to irrigate, she says.

“Considering irrigation water is potable—meaning it is the same limited source of drinking water we share—the stakes are pretty significant,” she says. “Not to mention the incredible quantity of water that can be saved and the related monetary savings on utility bills.”

The study appears in Urban Water Journal.

Source: University of Florida

Researchers have discovered for the first time how deadly hard-to-treat breast cancers persist after chemotherapy.

The findings reveal why patients with these cancers don’t respond well to immunotherapies designed to clear out remaining tumor cells by revving up the immune system.

Thanks to advances in cancer therapies, most forms of breast cancer are highly treatable, especially when caught early.

But the last frontier cases—those that can’t be treated with hormone or targeted therapies and don’t respond to chemotherapy—remain the deadliest and hardest to treat.

The process of surviving chemotherapy triggers a program of immune checkpoints that shield breast cancer cells from different lines of attack by the immune system. It creates a “whack-a-mole” problem for immunotherapy drugs called checkpoint inhibitors that may kill tumor cells expressing one checkpoint but not others that have multiple checkpoints, according to a new study published in the journal Nature Cancer.

“Breast cancers don’t respond well to immune checkpoint inhibitors, but it has never really been understood why,” says corresponding author James Jackson, associate professor of biochemistry and molecular biology at Tulane University School of Medicine.

“We found that they avoid immune clearance by expressing a complex, redundant program of checkpoint genes and immune modulatory genes. The tumor completely changes after chemotherapy treatment into this thing that is essentially built to block the immune system.”

Researchers studied the process in mouse and human breast tumors and identified 16 immune checkpoint genes that encode proteins designed to inactivate cancer-killing T-cells.

“We’re among the first to actually study the tumor that survives post-chemotherapy, which is called the residual disease, to see what kind of immunotherapy targets are expressed,” says first author Ashkan Shahbandi, an MD/PhD student in Jackson’s lab.

The tumors that respond the worst to chemotherapy enter a state of dormancy—called cellular senescence—instead of dying after treatment. Researchers found two major populations of senescent tumor cells, each expressing different immune checkpoints activated by specific signaling pathways. They showed the expression of immune evasion programs in tumor cells required both chemotherapy to induce a senescent state and signals from non-tumor cells.

They tested a combination of drugs aimed at these different immune checkpoints. While response could be improved, these strategies failed to fully eradicate the majority of tumors.

“Our findings reveal the challenge of eliminating residual disease populated by senescent cells that activate complex immune inhibitory programs,” Jackson says.

“Breast cancer patients will need rational, personalized strategies that target the specific checkpoints induced by the chemotherapy treatment.”

Source: Tulane University

WASHINGTON — As Satellogic prepares to launch its latest imaging satellites, the company has slashed revenue projections, resulting in layoffs and delays in construction of a new factory.

Four NewSat satellites, built by Satellogic, are among the 114 payloads to be launched on SpaceX’s Transporter-6 dedicated smallsat rideshare mission. That mission is scheduled to launch Jan. 3 at 9:56 a.m. Eastern on a Falcon 9 from Cape Canaveral Space Force Station in Florida. Satellogic signed a contract with SpaceX in May 2022 to launch 68 satellites on an unspecified number of launches.

The four satellites will join 26 currently in operation by Satellogic that provide high-resolution imagery. The company, in a business update Dec. 15, said it expected to launch 18 to 21 satellites in 2023, giving it enough satellites to map the Earth every two weeks.

That business update, which included the company’s financial results from the first half of 2022, showed revenue lagging earlier projections. The company recorded $2.4 million in revenue in the first half of the year, primarily from two unnamed customers, according to filings with the Securities and Exchange Commission.

Satellogic said in its business update it was projecting revenues of $6-8 million for all of 2022, and an adjusted earnings before interest, taxes, depreciation and amortization (EBITDA) loss of $55-60 million. By contrast, in an analyst day presentation in November 2021, part of going public through a SPAC merger, Satellogic projected revenue of $47 million for 2022 and an adjusted EBITDA loss of $2 million.

Emiliano Kargieman, chief executive of Satellogic, acknowledged he was “disappointed” with the revenue from the first half of the year, but remained optimistic about the company’s long-term trajectory, citing an increase in demand for its imagery seen in the second half of the year. “Our bookings and current pipeline support continued strong growth into 2023,” he said in a Dec. 15 earnings call.

The company, which in November 2021 projected revenues of $132 million in 2023, growing to $787 million in 2025, now projects $30-50 million in revenues in 2023, increasing to $140-200 million in 2025. Satellogic projects an adjusted EDBITA loss of $20-35 million in 2023, reaching breakeven in 2024 and growing to positive $35-90 million in 2025.

Kargieman said the company now has a better idea of the sales cycle for its imagery and other products. “After another year of talking to customers, we’re extremely confident in the numbers that we’re guiding for next year,” he said.

The diminished revenues have forced the company to cut costs. That included laying off 18% of its workforce in the third quarter, reducing its staff to about 380 people. Rick Dunn, Satellogic’s chief financial officer, said the number of employees would remain “more or less flat” in 2023.

The company has also scaled back the growth of its constellation. In that November 2021 presentation, Satellogic projected having 111 satellites in orbit in 2023. The company will instead end 2023 with no more than 47 satellites, although Kargieman said in the call that some of the 10 satellites it launched in October 2020 could be retired by the end of 2023 as they reach the end of their three-year design life.

With those reduced projections, Satellogic has delayed completion of a new high-throughput satellite manufacturing facility it planned to open in 2022 in the Netherlands. That factory, which Satellogic said in late 2021 would be fully operational by the start of 2023, was designed to produce 25 satellites a quarter.

Kargieman said the company’s existing factory in Uruguay can produce 24 satellites a year, sufficient for its near-term needs. “Going forward, we can continue to grow that capacity,” he said, increasing it potentially by a factor of two or three. The Dutch factory will go into service when the company is ready to scale up the constellation to the 300 satellites needed for daily remapping of the Earth. “The exact timing is yet to be defined.”

Satellogic is now offering to sell satellites, rather than just imagery, to customers. Dunn projected that at least 25% of the company’s revenues in 2023 would come from this new “space systems” business line, although weighted towards the second half of the year.

The rest of the company’s revenues will continue to come from imagery sales as well as its “constellation as a service” or dedicated satellite constellation business line, where governments and other organizations pay to gain priority access to Satellogic’s constellation over a designated area. One example Kargieman cited was an agreement with the government of Albania announced in September to provide imagery over its territory. The three-year deal is worth $6 million and includes naming two NewSat satellites launching on Transporter-6 Albania-1 and -2.

Satellogic announced Dec. 13 a letter of intent with the Mexican space agency AEM for a similar constellation-as-a-service agreement, but the company did not disclose when the contract would be finalized or its anticipated value. However, the Indian space agency ISRO announced Dec. 30 that it met with AEM officials, who asked ISRO for assistance in building and launching a remote sensing satellite.

Satellogic, which raised $168 million when its SPAC merger closed in January 2022, projected having $78-82 million of cash on hand at the end of 2022. That is enough, Kargieman said, to get the company to breakeven in 2024. “We don’t require additional financing,” he said. “We’re really in control of how much we spend and how much we invest into our future business, so we don’t expect to be raising additional financing.”

WASHINGTON — A cubesat launched on Artemis 1 missed its original chance to go into orbit around the moon but could still carry out its primary mission if engineers fix its thrusters in the coming weeks.

The NASA-funded LunaH-Map spacecraft, a six-unit cubesat, was one of 10 cubesat secondary payloads flown on the Artemis 1 mission on the inaugural launch of the Space Launch System Nov. 16. Those payloads were deployed from the SLS upper stage several hours after liftoff.

In the months leading up to the liftoff there were concerns that the batteries on LunaH-Map might have drained during its long wait for launch. The cubesat could not be charged after it was secured on the rocket in the fall of 2021.

However, the batteries were in good condition when the spacecraft transmitted its first telemetry shortly after deployment. “Our batteries were at 70% state of charge,” said Craig Hardgrove, principal investigator for LunaH-Map at Arizona State University, during a presentation about the mission at the Fall Meeting of the American Geophysical Union Dec. 15. “That was in line with our very optimistic predictions.”

While the spacecraft had sufficient power, it ran into problems with its propulsion system. “We had a very brief window to fire our propulsion system and hit a lunar gravity assist to get back to the moon,” he said. However, the thrusters failed to operate as expected to enable that maneuver to go into lunar orbit.

LunaH-Map is equipped with a BIT-3 ion thruster from Busek that uses solid iodine fuel. Hardgrove said Doppler ranging data suggests that a valve is partially stuck, allowing some iodine through but not enough to generate the required thrust.

Spacecraft engineers are trying to correct the problem with heaters in the propulsion system to free up the valve. “The sticking is something that we knew about,” he said, suggesting it came from the long wait for the launch.

If the problem can be fixed by mid-January, he said the spacecraft could take an alternative trajectory to the moon, arriving in January 2024. After that, there are options for sending LunaH-Map to rendezvous with or fly by a near Earth asteroid.

Other spacecraft systems are working well, he said. The spacecraft’s primary instrument, a neutron spectrometer designed to look for water ice deposits at the lunar south pole, collected data as it flew by the moon five days after launch. “It shows that this instrument is capable of performing the science investigation that we had planned to do,” Hardgrove said.

LunaH-Map is not the only cubesat launched on Artemis 1 that suffered technical problems. A Japanese cubesat called OMOTENASHI that was designed to perform a “semi-hard” landing on the moon failed to generate enough power from its solar arrays to communicate with Earth and was declared a loss.

Controllers have struggled to contact the CubeSat to Study Solar Particles (CuSP), which also appeared to encounter a battery problem, and Near Earth Asteroid Scout, a cubesat with a solar sail to fly by an asteroid. Lockheed Martin’s LunIR cubesat encountered an “unexpected issue with our radio signal,” the company said Dec. 8, but still considered the mission a useful technology demonstration.

Hardgrove, in his conference talk, remained optimistic about LunaH-Map. “We’re not dead. We’re doing great,” he said. “I think we’re hopefully going to ignite our propulsion system soon.”