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These OptoAssays allow for the bidirectional, light-induced movement of biomolecules and the reading of test results without the need for additional mechanical washing steps.

An OptoAssay uses a sender and a receiver area, which are brought into contact by adding the test reagent. In the sender area, there is a special protein that reacts to light. This protein can either bind or release specific molecules, depending on the type of light it captures.

When an LED emits at a wavelength of 660 nanometers, the molecules bind to the protein. Upon switching to far-red light with a wavelength of 740 nanometers, the molecules detach from the protein. In the receiver area, there are antibodies specifically designed to recognize and capture the target protein in the test reagent.

Koo and his team tested CREME on another AI-powered DNN genome analysis tool called Enformer. They wanted to know how Enformer’s algorithm makes predictions about the genome. Koo says questions like that are central to his work.

“We have these big, powerful models,” Koo said. “They’re quite compelling at taking DNA sequences and predicting gene expression. But we don’t really have any good ways of trying to understand what these models are learning. Presumably, they’re making accurate predictions because they’ve learned a lot of the rules about gene regulation, but we don’t actually know what their predictions are based off of.”

With CREME, Koo’s team uncovered a series of genetic rules that Enformer learned while analyzing the genome. That insight may one day prove invaluable for drug discovery. The investigators stated, “CREME provides a powerful toolkit for translating the predictions of genomic DNNs into mechanistic insights of gene regulation … Applying CREME to Enformer, a state-of-the-art DNN, we identify cis-regulatory elements that enhance or silence gene expression and characterize their complex interactions.” Koo added, “Understanding the rules of gene regulation gives you more options for tuning gene expression levels in precise and predictable ways.”

Vanderbilt University researchers, led by alumnus Bryan Gitschlag, have uncovered groundbreaking insights into the evolution of mitochondrial DNA (mtDNA). In their paper in Nature Communications titled “Multiple distinct evolutionary mechanisms govern the dynamics of selfish mitochondrial genomes in Caenorhabditis elegans,” the team reveals how selfish mtDNA, which can reduce the fitness of its host, manages to persist within cells through aggressive competition or by avoiding traditional selection pressures. The study combines mathematical models and experiments to explain the coexistence of selfish and cooperative mtDNA within the cell, offering new insights into the complex evolutionary dynamics of these essential cellular components.

Gitschlag, an alumnus of Vanderbilt University, conducted the research while in the lab of Maulik Patel, assistant professor of biological sciences. He is now a postdoctoral researcher at Cold Spring Harbor Laboratory in David McCandlish’s lab. Gitschlag collaborated closely with fellow Patel Lab members, including James Held, a recent PhD graduate, and Claudia Pereira, a former staff member of the lab.

Sleep, fasting, exercise, green porridge, black coffee, a healthy social life—there is an abundance of advice out there on how to live a good, long life. Researchers are working hard to determine why some people live longer than others, and how we get the most out of our increasingly long lives.

Now researchers from the Center for Healthy Aging, Department of Cellular and Molecular Medicine at the University of Copenhagen have discovered that a particular protein known as OSER1 has a great influence on longevity. The research is published in the journal Nature Communications.

“We identified this protein that can extend longevity. It is a novel pro-longevity factor, and it is a protein that exists in various animals, such as fruit flies, nematodes, silkworms, and in humans,” says Professor Lene Juel Rasmussen, senior author behind the new study.

Macroautophagy (hereafter autophagy) is a cellular recycling process that degrades cytoplasmic components, such as protein aggregates and mitochondria, and is associated with longevity and health in multiple organisms. While mounting evidence supports that autophagy declines with age, the underlying molecular mechanisms remain unclear. Since autophagy is a complex, multistep process, orchestrated by more than 40 autophagy-related proteins with tissue-specific expression patterns and context-dependent regulation, it is challenging to determine how autophagy fails with age. In this review, we describe the individual steps of the autophagy process and summarize the age-dependent molecular changes reported to occur in specific steps of the pathway that could impact autophagy.

Her initial workup revealed enlarged mediastinal nodes, bilateral ground glass interstitial opacities with areas of septal thickening, an incidental 4-cm left lower lobe nodular mass, multiple hypermetabolic lesions in the liver (the largest was 2.8 cm with a standard uptake value of 43), and osseous metastatic disease.

Ultrasound-guided biopsy showed poorly differentiated metastatic lung adenocarcinoma (stage 4) with 5% tumor cells expressing PD-L1 and negative for EGFR/ALK gene alterations.

Summary: Researchers found that mutations in the Sox3 gene cause hypopituitarism, a condition where the pituitary gland produces insufficient hormones, leading to growth issues and infertility. In a study on mice, they discovered that Sox3 mutations affect brain cells called NG2 glia, which are essential for hormone production.

Treating the mice with aspirin or altering their gut microbiome restored NG2 glia levels and reversed hypopituitarism. These findings suggest that both aspirin and gut bacteria could be explored as potential treatments for people with Sox3 mutations or other hormone-related disorders.