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Diseases and Conditions

“Revolutionizing Cancer Treatment: AI-Powered Model Predicts Cell Activity in Tissues Over Time”

A team of scientists has developed a remarkable new approach to modeling how cells behave over time—using a digital “forecast” much like predicting the weather. By combining patient genomics with a groundbreaking plain-language “hypothesis grammar,” the researchers can simulate how cells communicate and evolve within tissues. These simulations allow scientists to digitally test how cancers grow, how immune systems respond, and even how treatments might work in individual patients.

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The new software combines genomics technologies with computational modeling to predict cell changes in behavior, such as communication between cells that could cause cancer cells to flourish.

Researchers at the University of Maryland School of Medicine’s Institute for Genome Sciences (IGS) co-led the study that published online on July 25 in the journal Cell. It is the result of a multi-year, multi-lab project at the interface of software development with important collaborations between bench and clinical team science researchers.

“This research eventually could lead to computer programs that could help determine the best treatment for cancer patients by essentially creating a ‘digital twin’ of the patient,” said Jeanette Johnson, PhD, a Postdoc Fellow at the Institute for Genome Sciences (IGS) at UMSOM and co-first author of this study.

The team used a plain-language “hypothesis grammar” that uses common language as a bridge between biological systems and computational models to simulate how cells act in tissue. This grammar allows scientists to use simple English language sentences to build digital representations of multicellular biological systems and enabled the team to develop computational models for diseases like cancer.

In breast cancer, the IGS team modeled an effect where the immune system cannot curtail tumor cell growth and instead promotes invasion and cancer spread. They adapted this computational modeling framework to simulate a real-world immunotherapy clinical trial of pancreatic cancer.

Using genomics data from untreated tissue samples of pancreatic cancer, the model predicted that each virtual “patient” had a different response to the immunotherapy treatment — showcasing the importance of cellular ecosystems for precision oncology.

The team used new spatial genomics technology to further demonstrate the ways fibroblasts communicate with tumor cells. The program allowed the scientists to follow the growth and progression of pancreatic tumors to invasion from real patient tissue.

“What makes these models so exciting to me as someone who studies immunology is that they can be informed, initialized, and built upon using both laboratory and human genomics data,” said Dr. Johnson.

The new grammar is open source so that all scientists can benefit from it. “By making this tool accessible to the scientific community, we are providing a path forward to standardize such models and make them generally accepted,” said Daniel Bergman, PhD, a scientist at IGS and Assistant Professor of Pharmacology and Physiology at UMSOM.

To demonstrate this generalizability, Genevieve Stein-O’Brien, PhD, the Terkowitz Family Rising Professor of Neuroscience and Neurology at Johns Hopkins School of Medicine (JHSOM) led researchers in using this approach in a neuroscience example in which the program simulated the creation of layers as the brain develops.

“With this work from IGS, we have a new framework for biological research since researchers can now create computerized simulations of their bench experiments and clinical trials and even start predicting the effects of therapies on patients,” said Mark T. Gladwin, MD, Vice President for Medical Affairs at the University of Maryland, Baltimore, and the John Z. and Akiko K. Bowers Distinguished Professor and UMSOM Dean.

The team of senior authors on this study include, Paul Macklin, PhD, Associate Dean for Undergraduate Education and Professor of Intelligent Systems Engineering at the Indiana School of Informatics, Computing and Engineering at Indiana University, Genevieve Stein-O’Brien, Bloomberg Assistant Professor of Neuroscience and Assistant Director Single-Cell Training and Analysis Center (STAC) at Johns Hopkins University, and Dr. Fertig are continuing efforts to disseminate this software and extend its integration with genomics data for automatic model formulation through the National Cancer Institute (NCI) Informatics Technology in Cancer Research Consortium, who funded this study. Additional benchmarking of this study and applications of the software to breast and pancreatic cancer are supported from numerous NCI grants, the Jayne Koskinas Ted Giovanis Foundation, the National Foundation for Cancer Research, the Cigarette Restitution Fund Program from the State of Maryland, and the Lustgarten Foundation.

Chronic Illness

The Hidden Link Between Sleep Schedule and Disease Risk

A global study of over 88,000 adults reveals that poor sleep habits—like going to bed inconsistently or having disrupted circadian rhythms—are tied to dramatically higher risks for dozens of diseases, including liver cirrhosis and gangrene. Contrary to common belief, sleeping more than 9 hours wasn’t found to be harmful when measured objectively, exposing flaws in previous research. Scientists now say it’s time to redefine “good sleep” to include regularity, not just duration, as biological mechanisms like inflammation may underlie these powerful sleep-disease links.

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The recent publication of a groundbreaking international study has shed new light on the often-overlooked connection between our sleep schedules and the risk of various diseases. The research, led by teams from Peking University and Army Medical University, analyzed objective sleep data from an impressive 88,461 adults in the UK Biobank, revealing significant associations between sleep traits and a staggering 172 diseases.

One of the key findings is that poor sleep regularity – including inconsistent bedtimes and irregular circadian rhythms – is a critical factor in disease risk. The study used actigraphy data to monitor participants’ sleep patterns over an average of 6.8 years, identifying that 92 diseases had more than 20% of their risk attributed to subpar sleep behavior.

Perhaps most concerning are the links between certain sleep habits and specific diseases. For instance, going to bed after 00:30 was found to increase the risk of liver cirrhosis by an alarming 2.57 times, while low interdaily stability (a measure of consistency in daily sleep patterns) raised the risk of gangrene by a staggering 2.61 times.

Interestingly, the study also challenged previous claims that “long sleep” (more than 9 hours) is inherently bad for our health. While subjective reports have suggested links between long sleep and stroke or heart disease, the objective data revealed only one such association – in this case, with an increased risk of certain diseases.

It’s possible that misclassification may be to blame for these previous findings: a shocking 21.67% of participants who reported sleeping more than 9 hours actually slept less than 6 hours, highlighting how often actual sleep time is confused with time spent in bed.

The lead author of the study, Prof. Shengfeng Wang, emphasized that the results underscore the importance of considering sleep regularity beyond just duration. As we strive to maintain good health, it’s essential to prioritize a consistent and predictable sleep schedule – a crucial factor often overlooked until now.

Future research will delve deeper into the causality of these associations and explore the impact of sleep interventions on chronic disease outcomes. By shedding more light on this critical aspect of our overall well-being, we can work towards developing targeted strategies for promoting healthy sleep habits and reducing disease risk.

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Cancer

Turning Yogurt into a Healing Gel: Columbia Scientists Pioneer New Regenerative Medicine Approach

Scientists at Columbia Engineering have developed an injectable hydrogel made from yogurt-derived extracellular vesicles (EVs) that could revolutionize regenerative medicine. These EVs serve both as healing agents and as structural components, eliminating the need for added chemicals. The innovation leverages everyday dairy products like yogurt to create a biocompatible material that mimics natural tissue and enhances healing.

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The researchers at Columbia Engineering have achieved a groundbreaking feat in regenerative medicine. By leveraging milk-derived extracellular vesicles (EVs) from yogurt, they’ve created an injectable hydrogel that not only mimics human tissue but also actively promotes healing and tissue regeneration without additional chemical additives. This innovative approach marks a significant milestone in addressing longstanding barriers in biomaterial development for regenerative medicine.

Led by Santiago Correa, assistant professor of biomedical engineering at Columbia Engineering, the team designed a hydrogel system where EVs play a dual role: they serve as bioactive cargo, carrying hundreds of biological signals, and also act as essential structural building blocks, crosslinking biocompatible polymers to form an injectable material. This design space allows for the generation of hydrogels that incorporate EVs as both structural and biological elements.

The team’s unconventional approach using yogurt EVs overcame yield constraints that hindered the development of EV-based biomaterials. The resulting hydrogel was found to be biocompatible, drive potent angiogenic activity within one week in immunocompetent mice, and promote tissue repair processes without adverse reactions.

“The project started as a basic question about how to build EV-based hydrogels,” said Correa. “Yogurt EVs gave us a practical tool for that, but they turned out to be more than a model. We found that they have inherent regenerative potential, which opens the door to new, accessible therapeutic materials.”

This study demonstrates the power of cross-disciplinary, global partnerships in advancing biomaterials innovation. The team’s collaboration with researchers from the University of Padova and Kam Leong, a fellow Columbia Engineering faculty member, further strengthened their findings.

As Correa’s team explores the therapeutic potential of this hydrogel, they are also examining how it creates a unique immune environment enriched in anti-inflammatory cell types, which may contribute to observed tissue repair processes. This research opens new possibilities for regenerative medicine and highlights the exciting advancements in biomedical engineering.

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Cancer

Safer Non-Stick Coatings: Scientists Develop Alternative to Teflon

Scientists at the University of Toronto have developed a new non-stick material that rivals the performance of traditional PFAS-based coatings while using only minimal amounts of these controversial “forever chemicals.” Through an inventive process called “nanoscale fletching,” they modified silicone-based polymers to repel both water and oil effectively. This breakthrough could pave the way for safer cookware, fabrics, and other products without the environmental and health risks linked to long-chain PFAS.

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The scientific community has been working towards developing safer alternatives to per- and polyfluoroalkyl substances (PFAS), a family of chemicals commonly used in non-stick coatings. Researchers at the University of Toronto Engineering have made significant progress in this area by creating a new material that repels both water and grease about as well as standard PFAS-based coatings, but with much lower amounts of these chemicals.

Professor Kevin Golovin and his team have been working on developing alternative materials to replace Teflon, which has been used for decades due to its non-stick properties. However, the chemical inertness that makes Teflon so effective also causes it to persist in the environment and accumulate in biological tissues, leading to health concerns.

The researchers’ solution is a material called polydimethylsiloxane (PDMS), often sold as silicone. They have developed a new chemistry technique called nanoscale fletching, which bonds short chains of PDMS to a base material, resembling bristles on a brush. To improve the oil-repelling ability, they added the shortest possible PFAS molecule, consisting of a single carbon with three fluorines on it.

When coated on a piece of fabric and tested with various oils, the new coating achieved a grade of 6, placing it on par with many standard PFAS-based coatings. While this may seem like a small improvement, it’s a crucial step towards creating safer alternatives to Teflon and other PFAS-based materials.

The team is now working on further improving their material, aiming to create a substance that outperforms Teflon without using any PFAS at all. This would be a significant breakthrough in the field, paving the way for the development of even safer non-stick coatings for consumer products.

In conclusion, scientists have made significant progress in developing a safer alternative to Teflon and other PFAS-based materials. The new material has shown promising results, and further research is needed to improve its performance and scalability. As we move forward, it’s essential to prioritize the development of safe and sustainable technologies that minimize harm to both humans and the environment.

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