Lifeboat Foundation

Lung adenocarcinoma is the most common lung cancer and the cause of most cancer-related deaths in the United States. There are several ways lung adenocarcinoma can arise, one of which is a mutation in a protein called EGFR (epidermal growth factor receptor). Non-mutated EGFR helps cells grow in response to injury, but mutated EGFR promotes out-of-control growth that can turn into cancer.

Modern immunotherapies don’t work against EGFR-driven lung adenocarcinoma, and while some drugs exist to treat the cancer, patients typically develop a resistance to them within just a few years. This gap in the treatment tool chest inspired Salk Institute researchers to probe for weak spots in the cancer’s growth pathway.

The team discovered that EGFR-driven lung adenocarcinoma hijacks a specialized population of lung-resident immune cells called macrophages, which are designed to dispose of diseased and damaged cells, as well as maintain a delicate balance of protective lipids (fats) around lung alveoli, which are essential for breathing.

A theoretical study finds that the most energy-efficient way to control an active-matter system is to drive it at finite speed—unlike passive-matter systems.

The control of active matter, a class of systems in which each constituent constantly converts energy into directed motion, holds great potential for applications ranging from the targeted delivery of drugs to the creation of smart materials. Using an active-matter system to achieve a particular goal requires that one can efficiently drive it from one state to another. However, active matter’s intrinsic nonequilibrium condition presents a major challenge for theoretical treatments, meaning the most efficient way of driving a system is often difficult to predict. Now Luke Davis at the University of Luxembourg and colleagues have introduced a general framework to determine thermodynamically optimal protocols to drive active systems between different states in a way that minimizes the associated heat dissipation [1].

A network-theory model, tested on the work of Johann Sebastian Bach, offers tools for quantifying the amount of information delivered to a listener by a musical piece.

Great pieces of music transport the audience on emotional journeys and tell stories through their melodies, harmonies, and rhythms. But can the information contained in a piece, as well as the piece’s effectiveness at communicating it, be quantified? Researchers at the University of Pennsylvania have developed a framework, based on network theory, for carrying out these quantitative assessments. Analyzing a large body of work by Johan Sebastian Bach, they show that the framework could be used to categorize different kinds of compositions on the basis of their information content [1]. The analysis also allowed them to pinpoint certain features in music compositions that facilitate the communication of information to listeners. The researchers say that the framework could lead to new tools for the quantitative analysis of music and other forms of art.

To tackle complex systems such as musical pieces, the team turned to network theory—which offers powerful tools to understand the behavior of discrete, interconnected units, such as individuals during a pandemic or nodes in an electrical power grid. Researchers have previously attempted to analyze the connections between musical notes using network-theory tools. Most of these studies, however, ignore an important aspect of communication: the flawed nature of perception. “Humans are imperfect learners,” says Suman Kulkarni, who led the study. The model developed by the team incorporated this aspect through the description of a fuzzy process through which a listener derives an “inferred” network of notes from the “true” network of the original piece.

A protein that has been widely studied owing to its association with neurodegenerative diseases such as amyotrophic lateral sclerosis (ALS) is also linked to medulloblastoma, a type of central nervous system cancer. Medulloblastoma is one of the most common and aggressive brain tumors in children, arising from undifferentiated cells during early neural development.

A study led by a group of Brazilian scientists has shown in vitro and in vivo that the gene VAPB is linked to cell proliferation in these tumors. An article on the study is published in the journal Scientific Reports.

The discovery points to a potential marker of severity and, after more research, a future therapeutic target. Medulloblastoma is currently treated with a combination of surgery to remove the tumor and radiation therapy and/or chemotherapy, both of which are aggressive and can cause long-lasting brain damage.

A common practice of prescribing anticoagulants to people who have had unexplained strokes should stop, according to a study led by researchers at Columbia, Weill Cornell Medicine, and the University of Washington and published in JAMA.

Anticoagulants were thought to prevent additional strokes in people whose initial stroke has an unknown cause but who have a heart condition, atrial cardiopathy, that resembles atrial fibrillation, a common cause of stroke.

“We know these drugs work for people with atrial fibrillation, so we thought that they would probably work for people with atrial cardiopathy as well,” says Mitchell Elkind, MD, professor of neurology at the Vagelos College of Physicians and Surgeons and one of the study’s leaders. “That was the basis for the trial.”

Tissue contamination distracts AI models from making accurate real-world diagnoses. Human pathologists are extensively trained to detect when tissue samples from one patient mistakenly end up on another patient’s microscope slides (a problem known as tissue contamination). But such contamination can easily confuse artificial intelligence (AI) models, which are often trained in pristine, simulated environments, reports a new Northwestern Medicine study.

“We train AIs to tell ‘A’ versus ‘B’ in a very clean, artificial environment, but, in real life, the AI will see a variety of materials that it hasn’t trained on. When it does, mistakes can happen,” said corresponding author Dr. Jeffery Goldstein, director of perinatal pathology and an assistant professor of perinatal pathology and autopsy at Northwestern University Feinberg School of Medicine.

“Our findings serve as a reminder that AI that works incredibly well in the lab may fall on its face in the real world. Patients should continue to expect that a human expert is the final decider on diagnoses made on biopsies and other tissue samples. Pathologists fear — and AI companies hope — that the computers are coming for our jobs. Not yet.”

A study at the University of Cologne’s CECAD Cluster of Excellence in Aging Research has identified a protein complex that is activated by defects in the spliceosome, the molecular scissors that process genetic information. Future research could lead to new therapeutic approaches to treat diseases caused by faulty splicing.

The genetic material, in the form of DNA, contains the information that is crucial for the correct functioning of every human and animal cell. From this information repository, RNA, an intermediate between DNA and protein, the functional unit of the cell, is generated. During this process, the genetic information must be tailored for specific cell functions. Information that is not needed (introns) is cut out of the RNA and the important components for proteins (exons) are preserved.

A team of researchers led by Professor Dr. Mirka Uhlirova at the University of Cologne’s CECAD Cluster of Excellence in Aging Research has now discovered that if the processing of this information no longer works properly, a protein complex (C/EBP heterodimer) is activated and directs the cell towards a dormant state, known as cellular senescence. The results appear under the title “Xrp1 governs the stress response program to spliceosome dysfunction” in Nucleic Acids Research.

Scientists have been making nanoparticles out of DNA strands for two decades, manipulating the bonds that maintain DNA’s double-helical shape to sculpt self-assembling structures that could someday have jaw-dropping medical applications.

The study of DNA nanoparticles, however, has focused mostly on their architecture, turning the genetic code of life into components for fabricating minuscule robots. A pair of Iowa State University researchers in the genetics, development, and cell biology department—professor Eric Henderson and recent doctoral graduate Chang-Yong Oh—hope to change that by showing nanoscale materials made of DNA can convey their built-in genetic instructions.

“So far, most people have been exploring DNA nanoparticles from an engineering perspective. Little attention has been paid to the information held in those DNA strands,” Oh said.

Researchers have created the first functional 3D-printed brain tissue that can develop and form connections in the same way as real human brain tissue.

This remarkable accomplishment by a team at the University of Wisconsin–Madison provides neuroscientists with a new tool for studying communication between brain cells and other parts of the human brain, potentially leading to better ways of treating diseases like Alzheimer’s and Parkinson’s.

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