In addition to its physical effects, Alzheimer’s causes psychological, social and economic ramifications not only for the people living with the disease, but also for those who love and care for them. Because its symptoms worsen over time, it is important for both patients and their caregivers to prepare for the eventual need to increase the amount of support as the disease progresses.

To that end, researchers at The University of Texas at Arlington have created a novel learning-based framework that will help Alzheimer’s patients accurately pinpoint where they are within the disease-development spectrum. This will allow them to best predict the timing of the later stages, making it easier to plan for future care as the disease advances.

“For decades, a variety of predictive approaches have been proposed and evaluated in terms of the predictive capability for Alzheimer’s disease and its precursor, mild cognitive impairment,” said Dajiang Zhu, an associate professor in computer science and engineering at UTA. He is lead author on a new peer-reviewed paper published open access in Pharmacological Research. “Many of these earlier prediction tools overlooked the continuous nature of how Alzheimer’s disease develops and the transition stages of the disease.”

In work supported by more than $2 million in grants from the National Institutes of Health and the National Institute on Aging, Zhu’s Medical Imaging and Neuroscientific Discovery research lab and Li Wang, UTA associate professor in mathematics, developed a new learning-based embedding framework that codes the various stages of Alzheimer’s disease development in a process they call a “disease-embedding tree,” or DETree. Using this framework, the DETree can not only predict any of the five fine-grained clinical groups of Alzheimer’s disease development efficiently and accurately but can also provide more in-depth status information by projecting where within it the patient will be as the disease progresses.

To test their DETree framework, the researchers used data from 266 individuals with Alzheimer’s disease from the multicenter Alzheimer’s Disease Neuroimaging Initiative. The DETree strategy results were compared with other widely used methods for predicting Alzheimer’s disease progression, and the experiment was repeated several times using machine learning-methods to validate the technique.

“We know individuals living with Alzheimer’s disease often develop worsening symptoms at very different rates,” Zhu said. “We’re heartened that our new framework is more accurate than the other prediction models available, which we hope will help patients and their families better plan for the uncertainties of this complicated and devastating disease.”

He and his team believe that the DETree framework has the potential to help predict the progression of other diseases that have multiple clinical stages of development, such as Parkinson’s disease, Huntington’s disease, and Creutzfeldt-Jakob disease.

In new research published in the journal Science Advances, a team led by UCLA and The University of Oslo shows that at some point, the crater filled with water, depositing layers of sediments on the crater floor. The lake subsequently shrank and sediments carried by the river that fed it formed an enormous delta. As the lake dissipated over time, the sediments in the crater were eroded, forming the geologic features visible on the surface today.

The periods of deposition and erosion took place over eons of environmental changes, the radar indicates, confirming that inferences about the Jezero crater’s geologic history based on Mars images obtained from space are accurate.

“From orbit we can see a bunch of different deposits, but we can’t tell for sure if what we’re seeing is their original state, or if we’re seeing the conclusion of a long geological story,” said David Paige, a UCLA professor of Earth, planetary and space sciences and first author of the paper. “To tell how these things formed, we need to see below the surface.”

The rover, which is about the size of a car and carries seven scientific instruments, has been exploring the 30-mile-wide crater, studying its geology and atmosphere and collecting samples since 2021. Perseverance’s soil and rock samples will be brought back to Earth by a future expedition and studied for evidence of past life.

Between May and December 2022, Perseverance drove from the crater floor onto the delta, a vast expanse of 3 billion-year-old sediments that, from orbit, resembles the river deltas on Earth.

As the rover drove onto the delta, Perseverance’s Radar Imager for Mars’ Subsurface Experiment, or RIMFAX, instrument fired radar waves downward at 10-centimeter intervals and measured pulses reflected from depths of about 20 meters below the surface. With the radar, scientists can see down to the base of the sediments to reveal the top surface of the buried crater floor.

Years of research with ground-penetrating radar and testing of RIMFAX on Earth have taught scientists how to read the structure and composition of subsurface layers from their radar reflections. The resulting subsurface image shows rock layers that can be interpreted like a highway road cut.

“Some geologists say that the ability of radar to see under the surface is kind of like cheating,” said Paige, who is RIMFAX’s deputy principal investigator.

RIMFAX imaging revealed two distinct periods of sediment deposition sandwiched between two periods of erosion. UCLA and the University of Oslo report that the crater floor below the delta is not uniformly flat, suggesting that a period of erosion occurred prior to the deposition of lake sediments. The radar images show that the sediments are regular and horizontal — just like sediments deposited in lakes on Earth. The existence of lake sediments had been suspected in previous studies, but has been confirmed by this research.

A second period of deposition occurred when fluctuations in the lake level allowed the river to deposit a broad delta that once extended far out into the lake, but has now eroded back closer to the river’s mouth.

“The changes we see preserved in the rock record are driven by large-scale changes in the Martian environment,” Paige said. “It’s cool that we can see so much evidence of change in such a small geographic area, which allows us extend our findings to the scale of the entire crater.”

“Hematopoietic stem cells, or HSCs, produce blood and immune cells, but not all HSCs are equally productive,” said the study’s corresponding author Rong Lu, PhD, who is an associate professor of stem cell biology and regenerative medicine, biomedical engineering, medicine, and gerontology at USC, and a Leukemia & Lymphoma Society Scholar. “We wanted to understand the mechanism of why some stem cells produce more immune cells, while other stem cells produce fewer.”

With this goal in mind, first author Du Jiang, PhD, and his colleagues in the in the Lu Lab at the Keck School of Medicine of USC pioneered new techniques for understanding the quantitative association between immune cell production and gene expression in lab mice. The scientists labeled individual stem cells with genetic “barcodes” to track their immune cell production. They then correlated the barcode tracking with measurements of gene expression activity. They also developed innovative bioinformatics approaches to characterize their quantitative association.

By leveraging these technical advances, the scientists identified nearly 40 genes — including genes associated with diseases such as myelodysplastic syndrome, a type of cancer caused by abnormal blood-forming cells — that are related to immune cell production. They discovered associations between the activity of these genes and both the quantity and variety of immune cells produced. For example, certain genes are associated with the production of lymphoid cells, others with myeloid cells, and still others with a healthy balance of various immune cell types.

A few of the genes showed what the scientists described as a “constant association” with the production of lymphocytes only. In other words, at any level of lymphocyte output, gene expression was always associated with lymphocyte production.

A few other genes had a “discrete association” with the production of lymphocytes only. This means that gene activity was associated with lymphocyte production within a specific range of lymphocyte output levels.

Most commonly, genes would have either a “unimodal or multimodal” association with immune cell production. In these instances, which involved both lymphoid and myeloid cells, gene activity was only associated with immune cell production at either one or multiple specific levels of immune cell production.

“In this study, we show that most genes associated with immune cell production are associated only at specific levels of immune cell production,” said Jiang, who earned his PhD in the Lu Lab.”Our findings can inform strategies to optimize bone marrow transplantation — for example, by selecting donor bone marrow cells with gene activity associated with high and balanced levels of immune cell production.”

Additional authors include Adnan Y. Chowdhury, Anna Nogalska, Jorge Contreras, Yeachan Lee, Mary Vergel-Rodriguez, and Melissa Valenzuela from the Lu Lab.

The project was supported by federal funding from the National Institutes of Health (grants R00HL113104, R01HL138225, R01HL135292, R01HL135292-S1, R35HL150826, and R01AG080982) and the National Cancer Institute (grant P30CA014089). Additional support came from the Leukemia & Lymphoma Society (grant LLS-1370-20), California Institute for Regenerative Medicine, and the Hearst Foundations.

In some tropical regions, however, productivity is high even when the upwelling favourablewinds are weak. An international team of researchers has now investigated the physical mechanisms driving the upwelling off the coast of Angola. They found that the combination of coastal trapped waves and increased mixing on the shelf control productivity in this system. Their findings, published today in the journal Science Advances, could help predict the strength of seasonal productivity peaks.

“Productivity in the upwelling region off Angola shows strong seasonal fluctuations,” says corresponding author Mareike Körner, PhD student in the Research Unit Physical Oceanography at the GEOMAR Helmholtz Centre for Ocean Research Kiel. “The main upwelling season occurs in austral winter, from July to September. During this time, there is very high primary productivity in the waters off the Angolan coast, and correspondingly, there is a lot of fishing.”

Waves in the interior of the ocean play a crucial role for productivity, causing cold, nutrient-rich water to move up and down on seasonal time scales. These waves are not generated locally off the coast of Angola but originate at the equator. There, seasonal wind fluctuations create waves that travel east along the equator. Once they reach the eastern boundary of the equatorial Atlantic, they excite coastal trapped waves, which propagate polewards along the African coast. On their way, these coastal trapped waves transport nutrient-rich waters onto the Angolan shelf. Strong tidal mixing on the shelf brings the nutrients to the surface, where a phytoplankton bloom is induced. These plankton blooms can vary from year to year, depending on the intensity and arrival time of the coastal trapped waves.

For their study, the researchers combined hydrographic, oxygen, nitrate and satellite data, and a regional ocean model.

Körner emphasises: “The upwelling off Angola is caused by waves that are excited at the equator and then propagate along the African coast. This provides a potential for predicting the strength and timing of the biological productivity peak off Angola on seasonal time scales.” A better understanding of the driving mechanisms in this southwest African coastal upwelling system is also crucial for assessing possible future changes, such as the effects of climate change or other human impacts, in this important marine ecosystem.

At GEOMAR “Upwelling in the Atlantic Ocean” is a research focus as part of the GEOMAR 2030 strategy. Since 2013 GEOMAR has been conducting research in the area and has established extensive cooperation with Angolan colleagues. Seven research cruises led by the Research Unit Physical Oceanography have provided extensive data on mixing and distribution of nutrients on the shelf. In addition, a subsurface mooring has been collecting data on various parameters such as current velocities, temperature, salinity and oxygen since 2013.

But today there is a tradeoff between how much high-resolution information an implanted device can measure and how long it can maintain recording or stimulation performances. Rigid, silicon implants with many sensors, can collect a lot of information but can’t stay in the body for very long. Flexible, smaller devices are less intrusive and can last longer in the brain but only provide a fraction of the available neural information.

Recently, an interdisciplinary team of researchers from the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS), in collaboration with The University of Texas at Austin, MIT and Axoft, Inc., developed a soft implantable device with dozens of sensors that can record single-neuron activity in the brain stably for months.

The research was published in Nature Nanotechnology.

“We have developed brain-electronics interfaces with single-cell resolution that are more biologically compliant than traditional materials,” said Paul Le Floch, first author of the paper and former graduate student in the lab of Jia Liu, Assistant Professor of Bioengineering at SEAS. “This work has the potential to revolutionize the design of bioelectronics for neural recording and stimulation, and for brain-computer interfaces.”

Le Floch is currently the CEO of Axoft, Inc, a company founded in 2021 by Le Floch, Liu and Tianyang Ye, a former graduate student and postdoctoral fellow in the Park Group at Harvard. Harvard’s Office of Technology Development has protected the intellectual property associated with this research and licensed the technology to Axoft for further development.

To overcome the tradeoff between high-resolution data rate and longevity, the researchers turned to a group of materials known as fluorinated elastomers. Fluorinated materials, like Teflon, are resilient, stable in biofluids, have excellent long-term dielectic performance, and are compatible with standard microfabrication techniques.

The researchers integrated these fluorinated dielectric elastomers with stacks of soft microelectrodes — 64 sensors in total — to develop a long-lasting probe that is 10,000 times softer than conventional flexible probes made of materials engineering plastics, such as polyimide or parylene C.

The team demonstrated the device in vivo, recording neural information from the brain and spinal cords of mice over the course of several months.

“Our research highlights that, by carefully engineering various factors, it is feasible to design novel elastomers for long-term-stable neural interfaces,” said Liu, who is the corresponding author of the paper. “This study could expand the range of design possibilities for neural interfaces.”

The interdisciplinary research team also included SEAS Professors Katia Bertoldi, Boris Kozinsky and Zhigang Suo.

“Designing new neural probes and interfaces is a very interdisciplinary problem that requires expertise in biology, electrical engineering, materials science, mechanical and chemical engineering,” said Le Floch.

The research was co-authored by Siyuan Zhao, Ren Liu, Nicola Molinari, Eder Medina, Hao Shen, Zheliang Wang, Junsoo Kim, Hao Sheng, Sebastian Partarrieu, Wenbo Wang, Chanan Sessler, Guogao Zhang, Hyunsu Park, Xian Gong, Andrew Spencer, Jongha Lee, Tianyang Ye, Xin Tang, Xiao Wang and Nanshu Lu.

The work was supported by the National Science Foundation through the Harvard University Materials Research Science and Engineering Center Grant No. DMR-2011754.

Since nature has perfected its sensory systems over evolutionary time scales, an interdisciplinary team of researchers in the McKelvey School of Engineering at Washington University in St. Louis tapped into these capabilities to adapt the system on demand to perform at its peak performance. Their tools to achieve this goal: locusts and nanomaterials too small to see.

Srikanth Singamaneni and Barani Raman, both professors in the McKelvey School of Engineering, led a team that harnessed the power of specially made nanostructures that can absorb light and create heat, known as the photothermal effect, and act as containers to store and release chemicals on demand. They used these nanostructured materials to boost neural response in the locust’s brain to specific odors and to improve their identification. Results of the research were published in Nature Nanotechnology Jan. 25, 2024.

Singamaneni, the Lilyan & E. Lisle Hughes Professor in the Department of Mechanical Engineering & Materials Science, and Raman, professor of biomedical engineering, have collaborated for years with Shantanu Chakrabartty, the Clifford W. Murphy Professor in the Preston M. Green Department of Electrical & Systems Engineering, to harness the superior sensing capabilities of the locust olfactory system. Recently they demonstrated the feasibility of using a bio-hybrid electronic nose for sensing explosive vapors.

“We let the biology do the harder job of converting information about vaporous chemicals into an electrical neural signal,” Raman said. “These signals are detected in the insect antennae and are transmitted to the brain. We can place electrodes in the brain, measure the locusts’ neural response to odors, and use them as fingerprints to distinguish between chemicals.”

The idea, though sound, has a potential roadblock.

“We are limited by the number of electrodes and where we can place them,” Singamaneni said. “Since we will get only a partial signal, we want to amplify this signal. This is where we turned to heat and neuromodulation to enhance the signal we get.”

In the new research, the team used two strategies to boost the locusts’ ability to detect odors. First, the team created a biocompatible and biodegradable polydopamine nanoparticle that converts light to heat through a process called photothermal effect.

“Heat affects diffusion,” Raman said. “Imagine adding cold milk to hot coffee. The idea is to use the heat generated by nanostructures to locally heat, for example, a nanoheater, and enhance the neural activity.”

Second, these nanostructured materials can be made to load chemicals for storage. However, they need to be encapsulated by a covering material. The team used a phase-change material called tetradecanol which is solid at room temperature and transitions to liquid upon heating. When heated, the same nanoheaters will ooze the chemicals stored within them in addition to generating heat.

Singamaneni and the team stored octopamine, a neuromodulator involved in various functions, and released it on demand. Usually, these neuromodulators are released based on the needs of the organism. However, using the nanostructured heaters, they were released on demand to enhance the neural signals.

“Our study presents a generic strategy to reversibly enhance neural signals at the brain site where we place the electrodes,” Raman said.

“The nano-enabled neuromodulation strategy we developed opens new opportunities to realize tailored cyborg chemical sensing approaches,” said Prashant Gupta, a graduate student in Singamaneni’s lab and first author of the paper. “This approach would change an existing passive approach where information is simply read into an active one where the capabilities of the neural circuits as a basis for information processing are fully used.”