robo-naut

NASA names Rice University scientist to major Mars rover mission

A Rice University scientist will be working on the team for NASA's latest Mars rover. I

Image courtesy of NASA/JPL-Caltech

A Rice University Martian geologist has been chosen by NASA as one of the 13 scientists who will be working on a new Mars rover.

Perseverance is the rover that launched in July and is expected to land on Mars in February. It will be scouting for samples to bring back to study for ancient microbial life, and Kirsten Siebach — an assistant professor of Earth, Environmental and Planetary Sciences — will be among the researchers to work on the project. Her proposal was one of 119 submitted to NASA for funding, according to a Rice press release.

"Everybody selected to be on the team is expected to put some time into general operations as well as accomplishing their own research," she says in the release. "My co-investigators here at Rice and I will do research to understand the origin of the rocks Perseverance observes, and I will also participate in operating the rover."

Perseverance is headed for Jezero Crater, a 28-mile-wide area that once hosted a lake and river delta where, according to scientists, microbial life may have existed over 3 billion years ago. Siebach is particularly excited hopefully find fossils existing in atmospheric carbon dioxide dissolved in water — which usually exists as limestone on Earth.

"There are huge packages of limestone all over Earth, but for some reason it's extremely rare on Mars," she says. "This particular landing site includes one of the few orbital detections of carbonate and it appears to have a couple of different units including carbonates within this lake deposit. The carbonates will be a highlight of we're looking for, but we're interested in basically all types of minerals."

Siebach is familiar with rovers — she was a member of the team for NASA's Curiosity rover, which has been exploring Mars since 2012. For this new rover, Siebach knows what to expect.

"Because there is only one rover, the whole team at NASA has to agree about what to look at, or analyze, or where to drive on any given day," Siebach says in the release. "None of the rovers' actions are unilateral decisions. But it is a privilege to be part of the discussion and to get to argue for observations of rocks that will be important to our understanding of Mars for decades."

Siebach and her team — which includes Rice data scientist Yueyang Jiang and mineralogist Gelu Costin — are planning to tap into computational and machine-learning methods to map out minerals and discover evidence for former life on Mars. They will also be using a Planetary Instrument for X-ray Lithochemistry, or PIXL, to analyze the materials.

The return mission isn't expected to return until the early 2030s, so it's a long game for the scientists. However, the samples have the potential to revolutionize what we know about life on Mars with more context than before.

"Occasionally, something hits Mars hard enough to knock a meteorite out, and it lands on Earth," she says in the release. "We have a few of those. But we've never been able to select where a sample came from and to understand its geologic context. So these samples will be revolutionary."

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This story originally appeared on our sister site, InnovationMap.

A Rice University scientist will be working on the team for NASA's latest Mars rover. I

Image courtesy of NASA/JPL-Caltech

A Rice University scientist will be working on the team for NASA's latest Mars rover. I

technology science

brain scientists at work

Rice University scientists invent new algorithm to fight Alzheimer's

Vicky Yao and Qiliang Lai of Rice University work on a laptop.

Photo courtesy of Rice University

Vicky Yao, an assistant professor of computer science and member of the Ken Kennedy Institute at Rice University, and Qiliang Lai, a Rice postdoctoral researcher

A new breakthrough from researchers at Rice University could unlock the genetic components that determine several human diseases such as Parkinson's and Alzheimer's.

Alzheimer's disease affected 57 million people worldwide in 2021, and cases in the United States are expected to double in the next couple of decades. Despite its prevalence and widespread attention of the condition, the full mechanisms are still poorly understood. One hurdle has been identifying which brain cells are linked to the disease.

For years, it was thought that the cells most linked with Alzheimer's pathology via DNA evidence were microglia, infection-fighting cells in the brain. However, this did not match with actual studies of Alzheimer's patients' brains. It's the memory-making cells in the human brain that are implicated in the pathology.

To prove this link, researchers at Rice alongside Boston University developed a computational algorithm called “Single-cell Expression Integration System for Mapping genetically implicated Cell types," or SEISMIC. It allows researchers to zero in on specific neurons linked to Alzheimer's, the first of its kind. Qiliang Lai, a Rice doctoral student and the lead author of a paper on the discovery published in Nature Communications, believes that this is an important step in the fight against Alzheimer's.

“As we age, some brain cells naturally slow down, but in dementia ⎯ a memory-loss disease ⎯ specific brain cells actually die and can’t be replaced,” said Lai. “The fact that it is memory-making brain cells dying and not infection-fighting brain cells raises this confusing puzzle where DNA evidence and brain evidence don’t match up.”

Studying Alzheimer's has been hampered by the limitations of computational analysis. Genome-wide association studies (GWAS) and single-cell RNA sequencing (scRNA-seq) map small differences in the DNA of Alzheimer's patients. The genetic signal in these studies would often over-emphasize the presence of infection fighting cells, essentially making the activity of those cells too "loud" statistically to identify other factors. Combined with greater specificity in brain regional activity, SEISMIC reduces the data chatter to grant a clearer picture of the genetic component of Alzheimer's.

“We built our seismic algorithm to analyze genetic information and match it precisely to specific types of brain cells,” Lai said. “This enables us to create a more detailed picture of which cell types are affected by which genetic programs.”

Though the algorithm is not in and of itself likely to lead to a cure or treatment for Alzheimer's any time soon, the researchers say that SEISMIC is already performing significantly better than existing tools at identifying important disease-relevant cellular signals more clearly.

“We think this work could help reconcile some contradicting patterns in the data pertaining to Alzheimer’s research,” said Vicky Yao, assistant professor of computer science and a member of the Ken Kennedy Institute at Rice. “Beyond that, the method will likely be broadly valuable to help us better understand which cell types are relevant in different complex diseases.”

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