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Functional plasticity of RNA-binding proteins in cancer: both friend and foe

Plasticity of RNA-binding proteins in cancer.

Extensive research has shown that RNA-binding proteins (RBPs) can influence all cancer hallmarks via post-transcriptional regulation of gene expression.

Many RBPs are considered to be prognostic markers in cancer, and are emerging as important targets for therapeutic intervention through the development of drugs targeting RBPs.

Multiple RBPs play contrasting roles across cancer contexts and can facilitate or suppress cancer depending on the type, subtype, or stage of cancer.

The ability of an RBP to bind to a substrate, and the consequences of binding, are highly dependent on cell type-specific modifications of RBPs, their substrates, and interacting regulatory proteins and RNAs. https://www.cell.com/trends/cancer/fulltext/S2405-8033(25)00253-5 https://sciencemission.com/plasticity-of-RBPs-in-cancer

RNA-binding proteins (RBPs) govern RNA-based post-transcriptional processes that generate the abundance and diversity of the proteome. RBPs have recently emerged as crucial cancer regulators that can influence multiple cancer hallmarks. However, many RBPs display remarkable variations across different tumor types and can exert both tumor-promoting and tumor-suppressive effects. These opposing roles are often attributed to context-dependency, but there is a distinct lack of clarity regarding what aspects of cellular context define the differences in the roles of RBPs. Given the recent development of RBP-targeted interventions, resolving this significant gap in the field could improve the selectivity and specificity of RBP biomarkers and therapies in cancer.

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Uptake, Adherence, and Attrition in Clinical Trials of Depression and Anxiety Apps: A Systematic Review and Meta-Analysis

A meta-analysis of RCTs found high uptake (92%) but moderate adherence (62%) to mental health apps among participants with depression or anxiety; posttest attrition averaged 18% and follow-up attrition 28%. Trials that included reminders, human contact, and omitted gamification saw lower dropout rates.

Question What are the expected rates of uptake, attrition, and adherence in randomized clinical trials of mental health apps for depression and anxiety?

Findings This systematic review and meta-analysis of 79 randomized trials found high rates of app uptake (94%) and moderate adherence (62%) among participants with depression or anxiety. Posttest attrition averaged 17%, and follow-up attrition was 27%.

Meaning These findings highlight the need to optimize app design and trial protocols to improve engagement and reduce attrition in digital interventions for depression and anxiety.

New on-switch for pain signaling pathway could lead to safer treatment and relief

Researchers at Tulane University, with a team of colleagues from eight other universities, have discovered a new nerve cell signaling mechanism that could transform our understanding of pain and lead to safer, more effective treatments.

The study, co-led by Matthew Dalva, director of the Tulane Brain Institute and professor of cell and in the School of Science and Engineering and Ted Price at the University of Texas at Dallas, reveals that neurons can release an enzyme outside the cell that switches on pain signaling after injury. The work, published in Science, offers new insight into how strengthen their connections during learning and memory.

“This finding changes our fundamental understanding of how neurons communicate,” Dalva said. “We’ve discovered that an enzyme released by neurons can modify proteins on the outside of other cells to turn on pain signaling—without affecting normal movement or sensation.”

Aging alters the protein landscape in the brain — diet can counteract this

A study by the Leibniz Institute on Aging – Fritz Lipmann Institute (FLI) in Jena shows that the chemical composition of proteins in the brain undergoes fundamental changes with aging. In particular, ubiquitylation—a process that marks proteins and thus controls their activity and degradation—undergoes drastic changes in the aging brain. Interestingly, a change in nutrition, such as short-term dietary restriction, can partially revert some of these molecular patterns. These findings open up new opportunities to better understand the aging process of the brain and related diseases.

Cerebrospinal fluid motion in the brain captured in remarkable detail

Cerebrospinal fluid (CSF) is a clear and watery liquid that flows in and around the brain and spinal cord. Its functions include protecting parts of the nervous system, delivering nutrients and removing metabolic waste.

Some neurological diseases, including Alzheimer’s disease, have been linked to the abnormal accumulation of proteins in the brain, which can cause damage to neurons. This accumulation of proteins could potentially be linked to variations in the flow of CSF in specific brain regions.

Researchers at Leiden University Medical Center, University of Amsterdam and the German Center for Neurodegenerative Diseases (DZNE) recently developed a new approach to study the motion of CSF, which is based on the widely used imaging technique magnetic resonance imaging (MRI).

Engineers repurpose a mosquito proboscis to create a 3D printing nozzle

When it comes to innovation, engineers have long proved to be brilliant copycats, drawing inspiration directly from nature. But now some scientists are moving beyond simple imitation to incorporating natural materials into their designs. Stuck for ideas on how to create ultra-fine, low-cost 3D printing nozzles, researchers at McGill University in Canada repurposed the proboscis of a deceased female mosquito to create a sustainable, high-resolution 3D printing tip.

The work is published in the journal Science Advances.

High-resolution 3D printing is a process that creates three-dimensional objects with extremely fine details and very smooth surfaces. The technology is used in numerous fields such as aerospace, dentistry and biomedical research. However, its level of precision comes at a steep cost. The tiny nozzles can cost more than $80 per tip and are made of metal or plastic, both of which are nonbiodegradable.

Machine learning algorithm rapidly reconstructs 3D images from X-ray data

Soon, researchers may be able to create movies of their favorite protein or virus better and faster than ever before. Researchers at the Department of Energy’s SLAC National Accelerator Laboratory have pioneered a new machine learning method—called X-RAI (X-Ray single particle imaging with Amortized Inference)—that can “look” at millions of X-ray laser-generated images and create a three-dimensional reconstruction of the target particle. The team recently reported their findings in Nature Communications.

X-RAI’s ability to sort through a massive number of images and learn as it goes could unlock limits in data-gathering, allowing researchers to see molecules up close—and perhaps even on the move. “There is really no limit” to the dataset size it can handle, said SLAC staff scientist Frédéric Poitevin, one of the study’s principal investigators.

How small can optical computers get? Scaling laws reveal new strategies

The research, published in Nature Communications, addresses one of the key challenges to engineering computers that run on light instead of electricity: making those devices small enough to be practical. Just as algorithms on digital computers require time and memory to run, light-based systems also require resources to operate, including sufficient physical space for light waves to propagate, interact and perform analog computation.

Lead authors Francesco Monticone, associate professor of electrical and computer engineering, and Yandong Li, Ph.D. ‘23, postdoctoral researcher, revealed scaling laws for free-space optics and photonic circuits by analyzing how their size must grow as the tasks they perform become more complex.

Nature-inspired hydrogel offers power-free thermal management

The poplar (Populus alba) has a unique survival strategy: when exposed to hot and dry conditions, it curls its leaves to expose the ventral surface, reflecting sunlight, and at night, the moisture condensed on the leaf surface releases latent heat to prevent frost damage. Plants have evolved such intricate mechanisms in response to dynamic environmental fluctuations in diurnal and seasonal temperature cycles, light intensity, and humidity, but there have been few instances of realizing such a sophisticated thermal management system with artificial materials.

Now, a KAIST research team has developed an artificial material that mimics the thermal management strategy of the poplar leaf, significantly increasing the applicability of power-free, self-regulating thermal management technology in applications such as building facades, roofs, and temporary shelters. The paper is published in the journal Advanced Materials.

The research team led by Professor Young Min Song of the School of Electrical Engineering, in collaboration with Professor Dae-Hyeong Kim’s team at Seoul National University, has developed a flexible hydrogel-based “Latent-Radiative Thermostat (LRT)” that mimics the natural heat regulation strategy of the poplar leaf.

Watching gold’s atomic structure change at 10 million times Earth’s atmospheric pressure

The inside of giant planets can reach pressures more than one million times the Earth’s atmosphere. As a result of that intense pressure, materials can adopt unexpected structures and properties. Understanding matter in this regime requires experiments that push the limits of physics in the laboratory.

In a recent paper published in Physical Review Letters, researchers at Lawrence Livermore National Laboratory (LLNL) and their collaborators conducted such experiments with gold, achieving the highest-pressure structural measurement ever made for the material. The results, which show gold switching structure at 10 million times the Earth’s atmospheric pressure, are essential for planetary modeling and fusion science.

“These experiments uncover the atomic rearrangements that occur at some of the most extreme pressures achievable in laboratory experiments,” said LLNL scientist and author Amy Coleman.

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