The Future of Fighting Disease: AI Detects Cancer and Viral Infections With Nanoscale Precision

AI Virus Detection Concept — AINU, an innovative AI, uses high-resolution imaging to identify changes in cells, potentially transforming how diseases like cancer and viral infections are diagnosed and monitored. Credit: SciTechDaily.com

Researchers have developed AINU, an AI that can differentiate between cancer and normal cells and detect early viral infections in cells using <span class="glossaryLink" aria-describedby="tt" data-cmtooltip="

nanoscale

The term "nanoscale" refers to dimensions that are measured in nanometers (nm), with one nanometer equaling one-billionth of a meter. This scale encompasses sizes from approximately 1 to 100 nanometers, where unique physical, chemical, and biological properties emerge that are not present in bulk materials. At the nanoscale, materials exhibit phenomena such as quantum effects and increased surface area to volume ratios, which can significantly alter their optical, electrical, and magnetic behaviors. These characteristics make nanoscale materials highly valuable for a wide range of applications, including electronics, medicine, and materials science.

” data-gt-translate-attributes=”[{"attribute":"data-cmtooltip", "format":"html"}]” tabindex=”0″ role=”link”>nanoscale-resolution images. This could lead to faster, more accurate disease diagnostics and better patient outcomes.

Researchers at the Centre for Genomic Regulation (CRG), the University of the Basque Country (UPV/EHU), Donostia International Physics Center (DIPC), and the Fundación Biofisica Bizkaia (FBB, located in Biofisika Institute) have developed an <span class="glossaryLink" aria-describedby="tt" data-cmtooltip="

artificial intelligence

Artificial Intelligence (AI) is a branch of computer science focused on creating systems that can perform tasks typically requiring human intelligence. These tasks include understanding natural language, recognizing patterns, solving problems, and learning from experience. AI technologies use algorithms and massive amounts of data to train models that can make decisions, automate processes, and improve over time through machine learning. The applications of AI are diverse, impacting fields such as healthcare, finance, automotive, and entertainment, fundamentally changing the way we interact with technology.

” data-gt-translate-attributes=”[{"attribute":"data-cmtooltip", "format":"html"}]” tabindex=”0″ role=”link”>artificial intelligence which can differentiate cancer cells from normal cells, as well as detect the very early stages of viral infection inside cells. The findings, published today (August 27) in a study in the journal Nature Machine Intelligence, pave the way for improved diagnostic techniques and new monitoring strategies for disease.

The tool, AINU (AI of the NUcleus), scans high-resolution images of cells. The images are obtained with a special microscopy technique called STORM, which creates a picture that captures many finer details than what regular microscopes can see. The high-definition snapshots reveal structures at nanoscale resolution.

A nanometer (nm) is one-billionth of a meter, and a strand of human hair is about 100,000 nm wide. The AI can detect rearrangements inside cells as small as 20 nm, or 5,000 times smaller than the width of a human hair. These alterations are too small and subtle for human observers to find with traditional methods alone.

HeLa Cancer Cell Super-Resolution Image — The image uses two colors to show specific nuclear components which allow researchers to see detailed structures within the cell nucleus at nanoscale resolution. Credit: Zhong Limei

Revolutionizing Disease Detection With AI

“The resolution of these images is powerful enough for our AI to recognize specific patterns and differences with remarkable <span class="glossaryLink" aria-describedby="tt" data-cmtooltip="

accuracy

How close the measured value conforms to the correct value.

” data-gt-translate-attributes=”[{"attribute":"data-cmtooltip", "format":"html"}]” tabindex=”0″ role=”link”>accuracy, including changes in how <span class="glossaryLink" aria-describedby="tt" data-cmtooltip="

DNA

DNA, or deoxyribonucleic acid, is a molecule composed of two long strands of nucleotides that coil around each other to form a double helix. It is the hereditary material in humans and almost all other organisms that carries genetic instructions for development, functioning, growth, and reproduction. Nearly every cell in a person’s body has the same DNA. Most DNA is located in the cell nucleus (where it is called nuclear DNA), but a small amount of DNA can also be found in the mitochondria (where it is called mitochondrial DNA or mtDNA).

” data-gt-translate-attributes=”[{"attribute":"data-cmtooltip", "format":"html"}]” tabindex=”0″ role=”link”>DNA is arranged inside cells, helping spot alterations very soon after they occur. We think that, one day, this type of information can buy doctors valuable time to monitor disease, personalize treatments and improve patient outcomes,” says ICREA Research Professor Pia Cosma, co-corresponding author of the study and researcher at the Centre for Genomic Regulation in Barcelona.

AINU is a convolutional neural network, a type of AI specifically designed to analyze visual data like images. Examples of convolutional neural networks include AI tools that enables users to unlock smartphones with their face, or others used by self-driving cars to understand and navigate environments by recognizing objects on the road.

In medicine, convolutional neural networks are used to analyse medical images like mammograms or CT scans and identify signs of cancer that might be missed by the human eye. They can also help doctors detect abnormalities in MRI scans or X-ray images, helping make a faster and more accurate diagnosis.

Training AINU for Cancer and Virus Detection

AINU detects and analyses tiny structures inside cells at the molecular level. The researchers trained the model by feeding it with nanoscale-resolution images of the nucleus of many different types of cells in different states. The model learned to recognize specific patterns in cells by analyzing how nuclear components are distributed and arranged in three-dimensional space.

For example, cancer cells have distinct changes in their nuclear structure compared to normal cells, such as alterations to how their DNA is organized or the distribution of enzymes within the nucleus. After training, AINU could analyze new images of cell nuclei and classify them as cancerous or normal based on these features alone.

The nanoscale resolution of the images enabled the AI detect changes in a cell’s nucleus as soon as one hour after it was infected by the herpes simplex <span class="glossaryLink" aria-describedby="tt" data-cmtooltip="

virus

A virus is a microscopic infectious agent that can replicate only inside the living cells of an organism. Viruses can infect all types of life forms, from animals and plants to microorganisms, including bacteria and archaea. Structurally, viruses consist of genetic material—either DNA or RNA—enclosed in a protective protein coat called a capsid, and sometimes a lipid envelope. They are uniquely distinguished by their simple, acellular organization and mode of reproduction, which involves hijacking the host cell's machinery to produce new virus particles. This process often results in disease in the host organism. Viruses are responsible for a wide range of diseases, including the common cold, influenza, HIV/AIDS, and COVID-19. Despite their pathogenic nature, viruses also play roles in ecological and evolutionary processes, influencing gene transfer and genetic diversity.

” data-gt-translate-attributes=”[{"attribute":"data-cmtooltip", "format":"html"}]” tabindex=”0″ role=”link”>virus type-1. The model could detect the presence of the virus by finding slight differences in how tightly DNA is packed, which happens when a virus starts to alter the structure of the cell’s nucleus.

Toward Clinical Application and Beyond

“Our method can detect cells that have been infected by a virus very soon after the infection starts. Normally, it takes time for doctors to spot an infection because they rely on visible symptoms or larger changes in the body. But with AINU, we can see tiny changes in the cell’s nucleus right away,” says Ignacio Arganda-Carreras, co-corresponding author of the study and Ikerbasque Research Associate at UPV/EHU and affiliated with the FBB-Biofisika Institute and the DIPC in San Sebastián/Donostia.

“Researchers can use this technology to see how viruses affect cells almost immediately after they enter the body, which could help in developing better treatments and vaccines. hospitals and clinics, AINU could be used to quickly diagnose infections from a simple blood or tissue sample, making the process faster and more accurate,” adds Limei Zhong, co-first author of the study and researcher at the Guangdong Provincial People’s Hospital (GDPH) in Guangzhou, China.

Overcoming Technical Limitations for Clinical Use

The researchers have to overcome important limitations before the technology is ready to be tested or deployed in a clinical setting. For example, STORM images can only be taken with specialized equipment normally only found in biomedical research labs. Setting up and maintaining the imaging systems required by the AI is a significant investment in both equipment and technical expertise.

Another constraint is that STORM imaging typically analyses only a few cells at a time. For diagnostic purposes, especially in clinical settings where speed and efficiency are crucial, doctors would need to capture many more numbers of cells in a single image to be able to detect or monitor a disease.

“There are many rapid advances in the field of STORM imaging which mean that microscopes may soon be available in smaller or less specialized labs, and eventually, even in the clinic. The limitations of accessibility and throughput are more tractable problems than we previously thought and we hope to carry out preclinical experiments soon,” says Dr. Cosma.

The Future of Stem Cell Research With AINU

Though clinical benefits might be years away, AINU is expected to accelerate scientific research in the short term. The researchers found the technology could identify stem cells with very high precision. Stem cells can develop into any type of cell in the body, an ability known as pluripotency. Pluripotent cells are studied for their potential in helping repair or replace damaged tissues.

AINU can make the process of detecting pluripotent cells quicker and more accurate, helping make stem cell therapies safer and more effective. “Current methods to detect high-quality stem cells rely on animal testing. However, all our AI model needs to work is a sample that is stained with specific markers that highlight key nuclear features. As well as being easier and faster, it can accelerate stem cell research while contributing to the shift in reducing animal use in science,” says Davide Carnevali, first author of the research and researcher at the CRG.

Reference: “A deep learning method that identifies cellular heterogeneity using nanoscale nuclear features” by Davide Carnevali, Limei Zhong, Esther González-Almela, Carlotta Viana, Mikhail Rotkevich, Aiping Wang, Daniel Franco-Barranco, Aitor Gonzalez-Marfil, Maria Victoria Neguembor, Alvaro Castells-Garcia, Ignacio Arganda-Carreras and Maria Pia Cosma, 27 August 2024, Nature Machine Intelligence.
DOI: 10.1038/s42256-024-00883-x