Atmospheric scientists, led by Jian Wang, have discovered that wind-blown snow in the central Arctic produces abundant fine sea salt aerosols, resulting in increased seasonal surface warming. 

The Arctic is a concerning outlier when it comes to global warming trends. It warms almost four times faster than the global average, and the role of aerosols in this warming is significant. Scientists have known for a long time that pollutants from other regions can build up in the Arctic atmosphere. This leads to a change in atmospheric chemistry, which absorbs sunlight and has an impact on local weather patterns, resulting in localized warming that melts ice and snow. While sea salt particles are the primary aerosol mass concentration, the mechanisms that produce them and their impact on the Arctic climate have yet to be fully understood.

Atmospheric scientists led by Jian Wang, director of the Center for Aerosol Science and Engineering and a professor of energy, environmental and chemical engineering at the McKelvey School of Engineering at Washington University in St. Louis, investigated the production and impact of sea salt aerosols on Arctic warming. Their results revealed abundant fine sea salt aerosol production from blowing snow in the central Arctic, increasing particle concentration and cloud formation.

“Over the past few decades, scientists have identified ‘Arctic haze’ as the primary source of aerosols in the Arctic during winter and spring. This haze results from the long-range transport of pollutants,” said Xianda Gong, first author on the study and a former postdoctoral researcher in Wang’s lab. “However, our study reveals that local blowing snow, which produces sea salt particles, contributes a more substantial fraction to the total aerosol population in the central Arctic.”

Wang’s team analyzed data collected by the Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC). Such observations are difficult to obtain — the MOSAiC expedition entailed international collaboration and freezing an icebreaker into the central Arctic ice pack to drift with the sea ice for an entire year — but essential to understanding the full picture of atmospheric conditions in the Arctic.

“The MOSAiC expedition let us observe how aerosols and clouds evolve over a year and led to this discovery,” Wang said. “Sea salt particles in the Arctic atmosphere aren’t surprising, since there are ocean waves breaking that will generate sea salt aerosols. But we expect those particles from the ocean to be pretty large and not very abundant.

“We found sea salt particles that were much smaller and in higher concentration than expected when there was blowing snow under strong wind conditions,” Wang said.

In the central Arctic, the coldest winter nights are the clearest, when heat from Earth can escape into space unimpeded. Under a cozy blanket of clouds, though, long-wave radiation gets trapped and contributes to warming, so any process that leads to increased cloud formation and lingering cloudiness also boosts surface temperatures. Small aerosol particles, including those fine sea salt aerosols produced by blowing snow that Wang’s team discovered, turn out to be very good for cloud formation.

“These sea salt particles can act as cloud condensation nuclei, leading to cloud formation,” Gong said. “Considering the absence of sunlight in the winter and spring Arctic, these clouds can trap surface long-wave radiation, thereby significantly warming the Arctic surface.”

Though scientists had not observed this phenomenon before, fine sea salt aerosols from blowing snow have always been part of the Arctic climate system. With this observational confirmation and systematic study, which revealed that sea salt particles produced from blowing snow account for about 30% of total aerosol particles, climate models can now be updated to include the effects of these fine particles.

“Model simulations that don’t include fine sea salt aerosols from blowing snow underestimate aerosol population in the Arctic,” Wang said. “Blowing snow happens regardless of human warming, but we need to include it in our models to better reproduce the current aerosol populations in the Arctic and to project future Arctic aerosol and climate conditions.”

The findings of this study suggest that model simulations of the Arctic atmosphere must include fine sea salt aerosols from blowing snow in order to accurately represent the aerosol population in the region. This is an encouraging development, as it means that scientists now have a better understanding of the Arctic atmosphere and can use this knowledge to develop more accurate models and predictions. With this new information, researchers can continue to work towards a more comprehensive understanding of the Arctic climate and its effects on the global environment.

The research findings have been featured on the cover of the journal 'Cancer Cell'. According to authors from CSIC and CNIO, cognitive loss in patients with brain metastases may be caused by the interference created by cancer in neuronal circuits. When cancer spreads in the brain, it changes brain chemistry, thus disrupting communication between neurons. This is a distinct hypothesis from the one accepted so far and has significant implications for the diagnosis and treatment of brain metastasis. The authors have employed artificial intelligence to demonstrate that metastasis modifies brain activity. 

Nearly half of all patients with brain metastasis experience cognitive impairment. Until now, it was thought that this was due to the physical presence of the tumor pressing on neural tissue. However, this ‘mass effect’ hypothesis is flawed because there is often no relationship between the size of the tumor and its cognitive impact. Small tumors can cause significant changes, and large tumors can produce mild effects. Why is this?

The explanation may lie in the fact that brain metastasis hacks the brain’s activity, a study featured on Cancer Cell’s cover shows for the first time.

The authors, from the Spanish National Research Council (CSIC) and the Spanish National Cancer Research Centre (CNIO), have discovered that when cancer spreads (metastasizes) in the brain, it changes the brain’s chemistry and disrupts neuronal communication—neurons communicate through electrical impulses generated and transmitted by biochemical changes in the cells and their surroundings. 

In this study, the laboratories of Manuel Valiente (CNIO) and Liset Menéndez de La Prida (Cajal Institute CSIC) have collaborated within the EU-funded NanoBRIGHT project, aimed at developing new technologies for the study of the brain, and with the participation of other funding agencies such as MICINN, AECC, ERC, NIH, and EMBO.

Demonstration with artificial intelligence

The researchers measured the electrical activity of the brains of mice with and without metastases and observed that the electrophysiological recordings of the two groups of animals with cancer were different from each other. To be sure that this difference was attributable to metastases, they turned to artificial intelligence. They trained an automatic algorithm with numerous electrophysiological recordings, and the model was indeed able to identify the presence of metastases. The system was even able to distinguish metastases from different primary tumors—skin, lung, and breast cancer.

These results show that metastasis does indeed affect the brain’s electrical activity in a specific way, leaving clear and recognizable signatures.

For the authors, the study represents a “paradigm shift” in the basic understanding of the development of brain metastases and has implications for the prevention, early diagnosis, and treatment of this pathology.

On the trail of drugs against neurocognitive effects

In addition to recording changes in brain electrical activity in the presence of metastasis, the researchers have begun to explore the biochemical changes that might explain this alteration. By analyzing the genes expressed in the affected tissues, they have identified a molecule, EGR1, that may play an important role in this process. This finding opens up the possibility of designing a drug to prevent or alleviate the neurocognitive effects of brain metastasis.

As Manuel Valiente, head of the CNIO’s Brain Metastasis Group explains, “Our multidisciplinary study challenges the hitherto accepted assumption that neurological dysfunction, which is very common in patients with brain metastasis, is due solely to the mass effect of the tumor. We suggest that these symptoms are a consequence of changes in brain activity resulting from tumor-induced biochemical and molecular alterations. This is a paradigm shift that could have important implications for diagnosis and therapeutic strategies.”

Liset Menéndez de la Prida, director of the Laboratory of Neural Circuits at the Cajal Institute (CSIC), says: “Using machine learning, we have been able to integrate all the data to create a model that allows us to know whether there is or not metastasis in a brain, just by looking at its electrical activity. This computational approach may even be able to predict subtypes of brain metastases at an early stage. It is a completely pioneering work that opens up an unexplored path.”

Both authors emphasize the multidisciplinary nature of this complex study that combines neuroscience, oncology, and computational analysis, each using a wide range of different techniques.

Cognitive study of patients and development of non-invasive techniques

The change in focus brought about by this result means that researchers now want to analyze the cognitive status of patients with brain metastasis much more systematically.

For Valiente, this is one of the most important next steps. The key to this will be the National Brain Metastasis Network (RENACER) initiated and coordinated by CNIO, which has already served to generate the largest collection of living brain metastasis samples in the world (with prior consent from patients, tissue samples collected during surgical interventions are made available to the international scientific community in the CNIO Biobank), and in which they will now introduce protocols for the neurocognitive assessment of the participating patients.

For her part, Liset Menéndez de La Prida will work on integrating the recording of brain activity with the analysis of the molecules involved, “in order to develop new diagnostic probes for brain tumors,” she says. This task is in line with the European NanoBRIGHT project, which aims to develop non-invasive techniques for studying the brain and treating its pathologies, and in which CSIC and CNIO are participating.

Another goal is to find drugs that protect the brain from cancer-induced disruptions in neuronal circuits, using the strategies described above. “We will look for molecules involved in metastasis-induced changes in neuronal communication, and evaluate them as possible therapeutic targets,” explains Valiente.

In addition to the artificial intelligence developed by the CSIC team, they will use the METPlatform technology designed by CNIO to evaluate the potential therapeutic activity of hundreds of compounds simultaneously on brain tissue samples affected by metastasis.

The results of this study highlight the potential of machine learning to transform the way we comprehend and cure brain tumors. By identifying the ways in which tumors disrupt the communication between neurons, scientists have paved the way for more effective treatments that target the root causes of the disease. This research showcases the power of science and technology in enhancing the lives of those impacted by brain tumors, and it serves as an inspiration for future research that will continue to push the boundaries of what is feasible.