Colon cancer remains a major global health concern, ranking third among the most diagnosed cancers and the leading cause of cancer-related death worldwide. One critical factor that makes treating colon cancer challenging is the presence of cancer stem cells.
Though typically present in small populations, these powerful cells drive tumor growth, resist standard treatments, and often contribute to relapse. They achieve this through their “stemness,” a set of properties that enable these cells to self-renew and differentiate into other cell types. Thus, understanding how stemness might be controlled at the molecular level is essential for developing effective therapies for colon cancer.
Over the past two decades, researchers have identified several key molecules involved in both the development of the colon and the progression of colon cancer. Among them are CDX1 and CDX2, two homeobox transcription factors that help establish and maintain the identity of intestinal epithelial cells.
Researchers from Cornell and Northwestern universities have developed a rapid, cell-free method for building nanoparticle vaccines that mimic viruses at the molecular level, offering a powerful new tool for responding to emerging pandemics.
By producing and folding full-length viral membrane proteins directly into synthetic lipid bubbles called liposomes, the technique creates vaccine candidates in hours, rather than weeks or months, and could pave the way for faster, more adaptable immunization strategies against deadly viruses like Nipah.
The research, presented in the paper “Cell-Free Expression of Nipah Virus Transmembrane Proteins for Proteoliposome Vaccine Design,” was published in the journal ACS Nano.
A new risk prediction tool developed by the American Heart Association (AHA) estimated cardiovascular disease (CVD) risk in a diverse patient cohort more accurately than current models, according to a recent study published in Nature Medicine.
The tool, called the Predicting Risk of Cardiovascular Disease EVENTs (PREVENT) equations which was developed in 2023, could help health care providers more accurately identify patients who have higher CVD risk and enhance preventive care efforts, according to Sadiya Khan, the Magerstadt Professor of Cardiovascular Epidemiology and co-first author of the study.
“Evaluating the new PREVENT equations in a diverse sample of patients is critical to provide primary care providers and cardiologists with further assurance that they can utilize these equations to accurately predict patients’ CVD risk, particularly in vulnerable populations,” said Khan, who is also an associate professor of Medical Social Sciences in the Division of Determinants of Health and of Preventive Medicine in the Division of Epidemiology.
Scientists know that many proteins and pathways are involved in the development and progression of neurodegenerative conditions such as Alzheimer’s disease, Parkinson’s disease and frontotemporal dementia (FTD), and that these proteins can be detected in the plasma of people with the conditions.
But it hasn’t been clear exactly which proteins are distinct to one disease vs. shared among two or more of them, adding to the difficulty both of diagnosing these complex diseases from blood samples and of developing effective treatments.
A new study by Washington University School of Medicine in St. Louis researchers, published in Nature Medicine, provides some answers. Led by Carlos Cruchaga, the Barbara Burton & Reuben Morriss III Professor in the Department of Psychiatry and director of the NeuroGenomics and Informatics Center at WashU Medicine, the researchers analyzed protein activity in more than 10,500 blood plasma samples from patients with Alzheimer’s disease, Parkinson’s disease or FTD.