Geologist major recognized as fall 2022 Dean's Medalist

December 21, 2022

Editor’s note: This story is part of a series of profiles of notable fall 2022 graduates.

During his childhood, Enzo Carrascal Marquez and his family traveled the various landscapes of his home country, Peru, visiting and exploring the desert, the mountain region and the jungle. This exposure to nature, along with his interest in science since primary school, prompted him to major in geology. School of Earth and Space Exploration Dean's Medalist Enzo Carrascal Marquez. Download Full Image

“During the middle of high school, I realized I wanted a career that would allow me to spend time in a laboratory doing research but at the same time travel and explore new places,” Carrascal said. “Geology is a major with that perfect balance.”

Carrascal was named the 2022 Fall Dean’s Medalist from the School of Earth and Space Exploration and graduated with a Bachelor of Science in geological sciences.

Carrascal came to ASU as a transfer student from the National University of Engineering in Peru to experience an international university and broaden his opportunities after graduation. He discovered a vast number of possibilities and paths for his major with the opportunity to explore several upper-division courses.

“In the School of Earth and Space Exploration, I expanded my knowledge of geosciences in a leading institution in research and enjoyed the wonders that this state has to offer,” Carrascal said.

He is also a recipient of the New American University Transfer Scholarship from ASU for multiple semesters, because of his academic performance as an incoming transfer student.

During his time at ASU, Carrascal worked as an undergraduate researcher in the lab with Dan Shim, professor in the School of Earth and Space Exploration.

“The original plan was for an undergraduate researcher to assist in our efforts to develop new sample synthesis methods for shock wave experiments,” Shim said. “Enzo ended up leading the effort and completed the project within 6 months which is much shorter than we anticipated.”

After graduation, Carrascal will apply to graduate school to continue his studies in geosciences and plans to begin work in Arizona within his major.

“I want to have experience in both academia and industry, to become a competent professional able to solve problems with a significant impact on society,” Carrascal said.

Here, he shares a few thoughts about his time at ASU. 

Question: Which professor taught you the most important lesson while at ASU?

Answer: I have to say that the professors at ASU are amazing, and my experience with SESE faculty has been enriching when reaching out for both academic and professional advising. I met Professor Duane DeVecchio in Dynamic Earth, a class in which I later became a teaching assistant working with him. By meeting him during office hours and classes I learned a lot of things, including the lesson of never limiting yourself when facing new challenges. By aiming for the highest, we move towards experiences that call for our best version, taking us to personal growth. I also thank professors Thomas Sharp, Dan Shim and Melanie Barboni who were important to me during this academic journey.

Q: What’s the best piece of advice you’d give to those still in school?

A: Get the most out of every experience you have in school, from classes to extracurricular activities. Trust in your capacity to find a balance between academic work and time for personal development/growth. Reach out to professors during office hours. Find a circle of mentors, friends and classmates that share your vision and passion for the things you do and the goals you envision.

Q: What was your favorite spot on campus, whether for studying, meeting friends, or just thinking about life?

A: I would spend time outside the Memorial Union working on assignments and casually meeting friends during the day. It is a versatile spot and gives you part of the college life experience. I also liked going to Noble Library to study and the grass fields to play soccer.

Q: If someone gave you $40 million to solve one problem on our planet, what would you tackle?

A: One of the topics I explored in upper-division classes was the power of remote sensing data, as in the case of satellite imagery, and the wide range of applications for society. Addressing the betterment of image resolution on current satellites and exploring the promising capabilities of hyperspectral imaging for Earth observation would have a significant impact on our capacity of monitoring changes in the surface of the Earth, such as reducing the spread of wildfires, early identification of threatening conditions for crops in agriculture, enhanced exploration of mineral resources and so much more.

Catherine Shappell

Digital communications specialist, School of Earth and Space Exploration


Study traces shared and unique cellular hallmarks found in 6 neurodegenerative diseases

December 21, 2022

A perplexing range of neurodegenerative diseases are known to attack distinct regions of the brain, causing severe cognitive and motor deficit. The combined impact of these (generally fatal) diseases has inflicted a devastating toll on society. New insights suggest many of these afflictions have their origin in a constellation of common processes, which play out in different ways as each disease develops. 

In a study appearing in the current issue of Alzheimer’s & Dementia: The Journal of the Alzheimer’ Association, corresponding author Carol Huseby of Arizona State University and her colleagues look at cellular alterations in six distinct neurodegenerative diseases: amyotrophic lateral sclerosis or Lou Gehrig's disease, Alzheimer’s disease, Friedreich’s ataxia, frontotemporal dementia, Huntington’s disease and Parkinson’s disease. Headshot of Carol Huseby. Carol Huseby is a researcher with the ASU-Banner Neurodegenerative Disease Research Center. Download Full Image

The study uses an innovative approach, which includes the machine learning analysis of RNA found in whole blood. By comparing multiple diseases, researchers can identify which RNA markers occur across several neurodegenerative diseases and which are unique to each disease.

“It appears that multiple neurodegenerative diseases harbor similar fundamental dysfunctional cellular processes,” says Huseby, a researcher with the ASU-Banner Neurodegenerative Disease Research Center. “Differences between diseases may be key to discovering regional cell-type vulnerabilities and therapeutic targets for each disease.” 

The blood samples used for the study were derived from a publicly available data set known as the Gene Expression Omnibus. Each of the six neurodegenerative diseases were probed. As the machine learning algorithm combed through thousands of genes, it assembled sets of RNA transcripts that optimally classified each disease, comparing the data with RNA samples from healthy patient blood.

The selected RNA transcripts reveal eight common themes across the six neurodegenerative diseases: transcription regulation, degranulation (a process involved in inflammation), immune response, protein synthesis, cell death or apoptosis, cytoskeletal components, ubiquitylation/proteasome (involved in protein degradation) and mitochondrial complexes (which oversee energy usage in cells). The eight cellular dysfunctions uncovered are associated with identifiable pathologies in the brain characteristic of each disease.

The study also identified uncommon transcripts for each disease, which may represent unexplored disease pathways. Such disease-specific outliers may be explored as a potential source of diagnostic biomarkers.

For example, while synaptic loss was a common feature in all six of the diseases analyzed, transcripts related to a phenomenon known as spliceosome regulation were only detected in the case of Alzheimer’s disease. (The spliceosome is a protein complex found in the cell nucleus, essential for proper cell function. Defective splicing of RNA is associated with disease.)

The investigation of blood biomarkers for neurodegenerative diseases, coupled with powerful statistical methods using artificial intelligence, has opened a new window on these serious afflictions. Blood can be easily sampled in living patients at all stages of health and disease, providing a powerful new tool for early diagnosis.

According to the United Nations, when all neurodegenerative diseases are considered, the global death toll may top a staggering 1 billion people. The course of many such diseases is protracted and pitiless, causing not only grave suffering to patients but a massive economic burden on health care systems. New methods of early diagnosis, improved treatments and possible methods of prevention are vitally needed.

Most neurodegenerative diseases, however, have been tricky to accurately diagnose and stubbornly resistant to treatment, including Alzheimer’s disease (AD), the leading cause of dementia. While genetic factors do play a role in the development of AD, most cases are regarded as sporadic, meaning the underlying causes are unclear. This is also the case with three other diseases highlighted in the study: frontotemporal dementia, ALS and Parkinson’s disease. Huntington’s disease and Friedreich’s ataxia appear to be genetically determined and are said to be familial.

The illustration shows the cell types and brain regions affected by six different neurodegenerative diseases: Friedreich's ataxia (purple); Huntington's disease (blue); frontotemporal dementia (yellow); amyotrophic lateral sclerosis (ALS), also known as motor neuron disease (MND) or Lou Gehrig's disease (green); Parkinson's disease (orange); and Alzheimer's disease (pink). Graphic by Shireen Dooling

Signposts of neurodegeneration are detectable in both the central nervous and peripheral vascular systems. The diseases may also migrate from their point of origin to distant brain regions, where they inflict most of their damage.

The study describes RNA clusters or trees selected by the machine learning process, which uncovers patterns of gene expression common to the six neurodegenerative diseases explored in the study as well as expression profiles that are distinct and disease dependent. Thousands of such trees are created and statistically compared by the machine learning algorithm, to pick out groupings of 20 transcripts that most closely align with known disease pathways in the diseases under study.

The findings offer clues about common cellular features that may play a role in jump-starting processes of neurodegeneration. The study also raises puzzling questions about how distinct disease forms ultimately develop from these common elements.

From the RNA transcripts extracted from blood, some 10,000 genes are expressed. The machine learning algorithm, known as Random Forest, categorizes the data and compares results with gene expression profiles known to be associated with disease-linked biological pathways.

Screening of whole blood and examination of the complete RNA profile can overcome the limitations of many other forms of testing, which are often less comprehensive as well as expensive, highly invasive and labor intensive. Diagnosis through whole blood, in contrast, can be carried out at low cost virtually anywhere in the world. Blood results can be tracked over time, providing a valuable window on disease progression. Research of this kind may also encourage new modes of treatment.

The results suggest a tantalizing possibility: Transcriptional changes shared by multiple disease types may provide the initial seeds that later develop into each of the distinct brain afflictions. The mechanisms responsible for these common factors germinating to produce diverse diseases and symptomologies, attacking different regions of the brain, remain a central puzzle to be solved.  

Future research will explore transcriptional impacts on neurons in addition to blood cells as well as the underlying mechanisms that set the stage for neurodegenerative diseases to develop and evolve their distinct pathologies.

Richard Harth

Science writer, Biodesign Institute at ASU