Anomaly in the deep sea

Extraordinary accumulation of rare atoms could improve geological dating methods

Helmholtz-Zentrum Dresden-Rossendorf

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Schematic depiction of production and incorporation of cosmogenic 10Be into ferromanganese crusts.

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Credit: HZDR / blrck.de

Beryllium-10, a rare radioactive isotope produced by cosmic rays in the atmosphere, provides valuable insights into the Earth's geological history. A research team from the Helmholtz-Zentrum Dresden-Rossendorf (HZDR), in collaboration with the TUD Dresden University of Technology and the Australian National University (ANU), has discovered an unexpected accumulation of this isotope in samples taken from the Pacific seabed. Such an anomaly may be attributed to shifts in ocean currents or astrophysical events that occurred approximately 10 million years ago. The findings hold the potential to serve as a global time marker, representing a promising advancement in the dating of geological archives spanning millions of years. The team presents its results in the scientific journal Nature Communications (DOI: 10.1038/s41467-024-55662-4).

Radionuclides are types of atomic nuclei (isotopes) that decay into other elements over time. They are used to date archaeological and geological samples, with radiocarbon dating being one of the most well-known methods. In principle, radiocarbon dating is based on the fact that living organisms continuously absorb the radioactive isotope carbon-14 (14C) during their lifetime. Once an organism dies, the absorption ceases, and the 14C content starts to decrease through radioactive decay with a half-life of approximately 5,700 years. By comparing the ratio of unstable 14C to stable carbon-12 (12C), researchers can determine the date of the organism's death.

Archaeological finds, such as bones or remnants of wood, can be dated quite accurately in this way. “However, the radiocarbon method is limited to dating samples no more than 50,000 years old,” explains HZDR physicist Dr. Dominik Koll. “To date older samples, we need to use other isotopes, such as cosmogenic beryllium-10 (10Be).” This isotope is created when cosmic rays interact with oxygen and nitrogen in the upper atmosphere. It reaches the Earth through precipitation and can accumulate on the seabed. With a half-life of 1.4 million years, 10Be decays into boron, allowing geological dating that can extend back over 10 million years.

Conspicuous accumulation of beryllium

Some time ago, Koll's research group examined unique geological samples retrieved from the Pacific Ocean at a depth of several kilometers. The samples consisted of ferromanganese crusts, primarily composed of iron and manganese, which had formed slowly but steadily over millions of years. To date the samples, the team analyzed the 10Be content using a highly sensitive method – Accelerator Mass Spectrometry (AMS) at HZDR. In this process, the sample is chemically purified before undergoing analysis for trace isotopes. Individual atoms from the sample are accelerated by high voltage, deflected by magnets, and then registered by specialized detectors. This method allows for the precise identification of 10Be, distinguishing it from other beryllium isotopes as well as molecules and isotopes with the same mass, such as boron-10.

When the research group evaluated the collected data, they were in for a surprise. “At around 10 million years, we found almost twice as much 10Be as we had anticipated,” reports Koll. “We had stumbled upon a previously undiscovered anomaly.” To eliminate any possibility of contamination, the experts analyzed additional samples from the Pacific, which also exhibited the same anomaly. This consistency allows the team to conclude that it is indeed a real phenomenon.

Ocean currents, stellar explosion or interstellar collision?

But how did such a striking increase in concentration come about 10 million years ago? Koll, who completed his doctorate at the TU Dresden and the ANU, proposes two possible explanations. One is related to the ocean circulation near Antarctica, which is thought to have changed drastically 10 to 12 million years ago. “This could have caused 10Be to be unevenly distributed across the Earth for a period of time due to the altered ocean currents,” explains the physicist. ”As a result, 10Be could have become particularly concentrated in the Pacific Ocean.”

The second hypothesis is astrophysical in nature. It suggests that the after-effects of a near-Earth supernova could have caused cosmic radiation to become temporarily more intense 10 million years ago. Alternatively, the Earth might have temporarily lost its protective solar shield – the heliosphere – due to a collision with a dense interstellar cloud, making it more vulnerable to cosmic radiation. ”Only new measurements can indicate whether the beryllium anomaly was caused by changes in ocean currents or has astrophysical reasons,” says Koll. ”That is why we plan to analyze more samples in the future and hope that other research groups will do the same.” If the anomaly were found all over the globe, the astrophysics hypothesis would be supported. On the other hand, if it were detected only in specific regions, the explanation involving altered ocean currents would be considered more plausible.

The anomaly could be extremely useful for geological beryllium dating. When comparing different archives for dating, one fundamental problem arises. Common time markers must be identified in all data sets so they can be properly synchronized with each other. Dominik Koll explains, “For periods spanning millions of years, such cosmogenic time markers do not yet exist. However, this beryllium anomaly has the potential to serve as such a marker.”

Publication:
D. Koll, J. Lachner, S. Beutner, S. Fichter, S. Merchel, G. Rugel, Z. Slavkovská, C. Vivo-Vilches, S. Winkler, A. Wallner: A cosmogenic 10Be anomaly during the late Miocene as independent time marker for marine archives, in Nature Communications, 2025 (DOI: 10.1038/s41467-024-55662-4)

Further information:
Dr. Dominik Koll | Institute of Ion Beam Physics and Materials Research at HZDR
Phone: +49 351 260 3804 | Email: d.koll@hzdr.de

Media contact:
Simon Schmitt | Head
Communications and Media Relations at HZDR
Phone: +49 351 260 3400 | Mobile: +49 175 874 2865 | Email: s.schmitt@hzdr.de

The Helmholtz-Zentrum Dresden-Rossendorf (HZDR) performs – as an independent German research center – research in the fields of energy, health, and matter. We focus on answering the following questions:

• How can energy and resources be utilized in an efficient, safe, and sustainable way?
• How can malignant tumors be more precisely visualized, characterized, and more effectively treated?
• How do matter and materials behave under the influence of strong fields and in smallest dimensions?

To help answer these research questions, HZDR operates large-scale facilities, which are also used by visiting researchers: the Ion Beam Center, the Dresden High Magnetic Field Laboratory and the ELBE Center for High-Power Radiation Sources.
HZDR is a member of the Helmholtz Association and has six sites (Dresden, Freiberg, Görlitz, Grenoble, Leipzig, Schenefeld near Hamburg) with almost 1,500 members of staff, of whom about 680 are scientists, including 200 Ph.D. candidates.

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Journal

Nature Communications

DOI

10.1038/s41467-024-55662-4 

Method of Research

Experimental study

Subject of Research

Not applicable

Article Title

A cosmogenic 10Be anomaly during the late Miocene as independent time marker for marine archives

Article Publication Date

10-Feb-2025

 

Princeton neuroscientists crack the code of how we make decisions

A new mathematical framework uncovers how the brain’s prefrontal cortex processes mixed signals to guide decision making, offering fresh insights for both clinical care and next-generation AI

Princeton University, Princeton Neuroscience Institute

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A new mathematical model sheds light on how the brain processes different cues, such as sights and sounds, during decision making. The findings from Princeton neuroscientists may one day improve how brain circuits go awry in neurological disorders, such as Alzheimer’s, and could help artificial brains, like Alexa or self-driving car technology, more helpful.

The findings were published February 10 in the journal Nature Neuroscience.

Walking to work, commuters encounter many sensory signals along their route, such as the glow of a crosswalk signal that indicates whether it’s safe to cross or beware of oncoming traffic. As the crude cartoon of a person walking lights up and people start to cross, a roaring ambulance might bolt down the block and towards the intersection. 

Precisely how the brain juggles conflicting and related sensory information, such as colored signals and loud sirens, and makes a sensible decision has been long studied but still a mystery. 

One brain region critical for decision making is the prefrontal cortex, which sits just behind the eyes and is lauded as the epicenter of higher cognition.

Previous research found that the response of single brain cells in the prefrontal cortex during decision-making is multifaceted and complex. For example, a neuron in the prefrontal cortex may only fire in response to a green traffic light when there is a car blocking the crosswalk. A unified understanding of how brain cells in the prefrontal cortex process sensory information, like traffic signals, and then generate behavioral outputs, like deciding to jaywalk, however, has eluded researchers. 

Different mathematical approaches have been used before to try to understand the circuit mechanisms linking neural dynamics to behavioral output, each with their own limitations. One approach center on recurrent neural networks, a type of neural circuit model that consists of many recurrently connected units. Recurrent neural networks can be trained to perform decision-making tasks, but the density of their recurrent connections makes them hard to interpret. 

In their recent paper, postdoctoral researcher Christopher Langdon, Ph.D., and assistant professor of neuroscience Tatiana Engel, Ph.D., propose a new mathematical framework to better explain decision making dubbed the latent circuit model. 

Instead of a complex recurrent neural network model, Langdon and Engel propose a sort of trees instead of the forest approach. To make sense of a large network of brain activity and trying to understand how each cell’s behavior is influenced by another, maybe just a few nerve cell ringleaders can explain the whole crowd’s activity and influence decision making, what neuroscientists call a “low-dimensional” mechanism.

“The goal of the research was to understand if low-dimensional mechanisms were operating inside large recurrent neural networks” Langdon said. 

To test their hypothesis, Langdon and Engel first applied their new model to recurrent neural networks trained to perform a context-dependent decision-making task.

The task, performed by humans, monkeys, or computers, begins with a shape on a screen (square vs. triangle, context cue), followed by a moving grid (sensory cue). Based on the shape, the participant is asked to report either the color (red vs. green) or the motion (left vs. right) of the moving grid.  

Using their new model, Langdon and Engel found that when motion was the important cue for participants to track, prefrontal cortex cells that process shape shut off neighboring cells that pay attention to color. The opposite was true when asked to discriminate red versus green.

“It was very exciting to find an interpretable, concreate mechanism hiding inside a big network,” Langdon said. 

The latent circuit model makes predictions about how choices should change when the strength of connections between different latent nodes is altered. This is powerful because it allows researchers to validate if latent connectivity structure is actually needed to support task performance. Indeed, the authors found that task performance suffered in predictable ways when removing specific connections in the circuit. 

“The cool thing about our new work is that we showed how you can translate all those things that you can do with a circuit onto a big network,” Langdon said. “When you build a small neural circuit by hand, there’s lots of things you can do to convince yourself you understand it. You can play with connections and perturb nodes, and have some idea what should happen to behavior when you play with the circuit in this way.”

The human brain, with more neurons than there are stars in the Milky Way, is dauntingly complex.  This new latent circuit model, though, opens new possibilities for revealing mechanisms that explain how connectivity amongst hundreds of brain cells gives rise to the computations that drive people to make different choices. 

Challenges with decision-making are a hallmark of several complex mental health disorders, ranging from depression to attention deficit hyperactive disorder. By revealing the mathematical computations performed by the brain to help people make decisions, these findings may lend itself to better understanding these challenging conditions, and for enhancing the decision-making capacity of technologies from digital assistants like Alexa to self-driving cars. The first steps, however, involve applying this new model to other decision-making tasks that are commonly used in the laboratory. 

“A lot of the tightly controlled decision-making tasks that experimentalist study, I believe that they likely have relatively simple latent mechanisms” Langdon said. “My hope is that we can start looking for these mechanisms now in those datasets.”  

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Journal

Nature Neuroscience

DOI

10.1038/s41593-025-01869-7 

Method of Research

Experimental study

Subject of Research

People

Article Title

Latent circuit inference from heterogeneous neural responses during cognitive tasks

Article Publication Date

10-Feb-2025

 

Bacteria, brains, and sugar: scientists uncover new connections

Using a new method to study how carbohydrates modify proteins, scientists have discovered that gut bacteria can alter molecular signatures in the brain

European Molecular Biology Laboratory

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A new study shows that gut bacteria can influence the molecular pattern of glycosylation – the presence of sugar groups on proteins – in the brain.

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Credit: Daniela Velasco Lozano/EMBL

Our guts are home to trillions of bacteria, and research over the last few decades has established how essential they are to our physiology – in health and disease. A new study from EMBL Heidelberg researchers shows that gut bacteria can bring about profound molecular changes in one of our most critical organs – the brain.

The new study, published in the journal Nature Structural and Molecular Biology, is the first to show that bacteria living in the gut can influence how proteins in the brain are modified by carbohydrates – a process called glycosylation. The study was made possible by a new method the scientists developed – DQGlyco – which allows them to study glycosylation at a much higher scale and resolution than previous studies.

A new way to measure glycosylation

Proteins are the workhorses of our cells and their main building blocks. Sugars, or carbohydrates, on the other hand, are among the body's main sources of energy. However, the cell also uses sugars to chemically modify proteins, altering their functions. This is called glycosylation.

“Glycosylation can affect how cells attach to each other (adhesion), how they move (motility), and even how they talk to one another (communication),” explained Clément Potel, first author of the study and Savitski Team Research Scientist. “It is involved in the pathogenesis of several diseases, including cancer and neuronal disorders.”

However, glycosylation has traditionally been notoriously difficult to study. Only a small portion of proteins in the cell are glycosylated and concentrating enough of them in a sample for studying (a process called ‘enriching’) tends to be laborious, expensive, and time-consuming. 

“So far, it's not been possible to do such studies on a systematic scale, in a quantitative fashion, and with high reproducibility,” said Mikhail Savitski, Team Leader, Senior Scientist, and Head of the Proteomics Core Facility at EMBL Heidelberg. “These are the challenges we managed to overcome with the new method.” 

DQGlyco uses easily available and low-cost laboratory materials, such as functionalised silica beads, to selectively enrich glycosylated proteins from biological samples, which can then be precisely identified and measured. Applying the method to brain tissue samples from mice, the researchers could identify over 150,000 glycosylated forms of proteins (‘proteoforms'), an increase of over 25-fold compared to previous studies.

The quantitative nature of the new method means that researchers can compare and measure differences between samples from different tissues, cell lines, species etc. This also allows them to study the pattern of 'microheterogeneity’ – the phenomenon where the same part of a protein can be modified by many (sometimes hundreds of) different sugar groups. 

One of the most common examples of microheterogeneity is human blood groups, where the presence of different sugar groups on proteins in red blood cells determines blood type (A, B, O, and AB). This plays a major role in deciding the success of blood transfusions from one individual to the other. 

The new method allowed the team to identify such microheterogeneity across hundreds of protein sites. “I think the widespread prevalence of microheterogeneity is something people had always assumed but that had never been clearly demonstrated, since you need to have enough coverage of glycosylated proteins to be able to make the statement,” said Mira Burtscher, another first author of the study and a Savitski Team PhD student.

From the gut to the brain

Given the method’s precision and power, the researchers decided to use it to address an outstanding biological question. In collaboration with Michael Zimmermann's group at EMBL, they next tested whether the gut microbiome had any effect on the glycosylation signatures they had observed in the brain. Both Zimmermann and Savitski are part of the Microbial Ecosystems Transversal Theme at EMBL, which was introduced by the 2022-26 EMBL programme 'Molecules to Ecosystems'. 

“It is known that gut microbiomes can affect neural functions, but the molecular details are largely unknown,” said Potel. “Glycosylation is implicated in many processes, such as neurotransmission and axon guidance, so we wanted to test if this was a mechanism by which gut bacteria influenced molecular pathways in the brain.”

Interestingly, the team found that when compared to 'germ-free mice’, i.e. mice grown in a sterile environment such that they completely lack any microbes in and on their body, mice colonised with different gut bacteria had different glycosylation patterns in the brain. The changed patterns were particularly apparent in proteins known to be important in neural functions, such as cognitive processing and axon growth. 

The study’s datasets are openly available via a new dedicated app for other researchers. In addition, the team is also curious whether the data can be used to inform predictions about glycosylation sites, especially in different species. For this, they have been using machine learning approaches such as AlphaFold – the AI-based tool for predicting protein structures recognised with the 2024 Nobel Prize in Chemistry.  

“By training the models on mouse data, we can start predicting what could be the variability of glycosylation sites in humans, for example,” said Martin Garrido, a postdoc in the Savitski and Saez-Rodriguez groups at EMBL and another first author of the study. “It could be very useful for people studying other organisms to help them identify glycosylation sites in their proteins of interest.”

The researchers are also working towards applying the new method to answer more fundamental biological questions and to understand the functional role glycosylation plays in cells. 

 

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Journal

Nature Structural & Molecular Biology

DOI

10.1038/s41594-025-01485-w 

Method of Research

Experimental study

Article Title

Uncovering protein glycosylation dynamics and heterogeneity using deep quantitative glycoprofiling (DQGlyco).

Article Publication Date

10-Feb-2025

 

Trump's 2024 election victory: A double-edged sword for the US stock market 

University of Surrey

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Financial markets are reacting not just to Donald Trump's return to the White House but also to the unpredictability of this victory, according to a new study from the University of Surrey.  Investors must diversify their portfolios to mitigate risks associated with political volatility and to remain vigilant about the potential for abrupt market corrections. 

A new study, published in Economics Letters, indicates that while there was an immediate surge in stock prices following Trump's election, this was quickly tempered by investor concerns over potential trade wars and international instability.  

A group of international researchers from the University of Surrey, Macquarie University, Australia, The Memorial University of Newfoundland, Canada and Paris School of Business, analysed the stock market response to Trump's decisive 2024 electoral win using a robust event study methodology. This involved examining the performance of over 1,500 publicly traded companies on the Standard & Poors' 1500 index, focusing on their stock price movements around the election date. The team observed significant abnormal returns, particularly among small-cap firms and specific sectors such as energy, which capitalised on anticipated regulatory changes. 

Dr Shaker Ahmed, lead author of the study and Lecturer in Finance at the University of Surrey, said: 

"Our findings highlight the complex landscape that investors navigate in the wake of major political events. While there is optimism surrounding pro-business policies, underlying fears of geopolitical conflicts can lead to volatility. Investors must prepare for a reality where gains can swiftly turn into losses." 

The research reveals a clear contrast between the "Hope Hypothesis" — the belief that Trump's policies would foster a business-friendly environment — and the "Fear Hypothesis," which warns of potential trade disruptions and uncertainty. The data shows that small-cap firms, primarily domestic, benefited most from this political shift, suggesting that investors are weighing their options carefully in this divided market. 

Dr Ahmed continued: 

"Understanding the implications of political events on market dynamics is crucial for informed investment strategies." 
 

[ENDS] 

Notes to editors:

• Dr Shaker Ahmed is available for interview, please contact mediarelations@surrey.ac.uk to arrange.   

• The full paper is available in in Economics Letters 

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Journal

Economics Letters

DOI

10.1016/j.econlet.2025.112170 

Method of Research

Observational study

Subject of Research

People

Article Title

The comeback effect: Market responses to Trump's 2024 election victory

 

New study reveals link between workaholism and organizational harm

Researchers found being a workaholic can cause people to become less engaged with their moral values

Aston University

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The hidden ethical costs of workaholism have been highlighted in a recent study led by Aston University and University of Leipzig scholars.

Workaholism is an inner pressure to working, that provides a sense of fulfilment but can lead to physical and psychological problems, relationship issues and burnout.

The study, published in the Journal of Organizational Behavior, showed that it can interfere with moral self-regulation and subsequent ethical behaviour, particularly in organisations that prioritise bottom-line results and self-interest.

An international team of researchers, led by Professor Roberta Fida (Aston University) and Dr Michael Knoll (University of Leipzig) and funded by INAIL (the Italian National Institute for Insurance against Accidents at Work), conducted two surveys to study workplace behaviour. They gathered responses from employees in Italy (505 people) and the UK (1,046 people) over three different points in time. Their findings show that being a workaholic can cause people to become less engaged with their moral values. This makes them less likely to speak up about ethical problems they notice at work and more likely to stay silent, even when they see something wrong.

The research draws on Bandura’s social cognitive theory of morality, which suggests that moral behaviour is regulated by personal standards and social norms. The researchers found that moral disengagement acts as a critical mediator between workaholism and employee silence or moral voice. Workaholism increases tendencies to morally disengage which, in turn, led to less moral voice and more employee silence.

Another finding surrounded the role of the organisational context. The second study revealed that a perceived climate of self-interest, where employees believe that individual gain is prioritised over other values such as norms or collective welfare, amplifies the negative effects of workaholism. In these environments, workaholics were even more prone to morally disengage, further diminishing their likelihood of addressing ethical issues.

Roberta Fida, professor of organisational behaviour and organisational psychology at Aston University, said:

“We often think of workaholism as a personal struggle or even a badge of dedication, but our research shows it has far-reaching consequences.

“Workaholics, focused intensely on task completion and personal achievement, tend to disengage from their moral standards.

“This leads them to rationalise silence in the face of unethical practices, which can preserve behaviours and practices that are potentially damaging to organisations and society at large.

“Our findings highlight the critical need for organisations to rethink their workplace cultures, particularly in sectors where bottom-line mentalities dominate. When workaholism and a self-interested culture converge, the result isn’t just burnout - it’s a systemic erosion of ethical standards.”

Dr Michael Knoll said:

“Workaholics justify withholding their voice by convincing themselves that their silence is harmless or justified as they need to prioritise finishing their tasks.

“But by doing so, they fail to address pressing organisational issues such as safety risks, unethical leadership, or inefficiencies that affect their colleagues and stakeholders.

“By normalising silence and neglecting ethical concerns, organisations risk perpetuating harm to employees, stakeholders, and society. It’s not just about individual well-being—it’s about organisational sustainability.

“Employers need to move beyond seeing long hours and over-dedication as signs of commitment. Instead, they should foster an organisational culture that rewards ethical behaviour, encourages moral voice, and reduces pressures that lead to excessive working.”

You can read the full study, Quiet workaholics? The link between workaholism and employee silence and moral voice as explained by the social cognitive theory of morality, by visiting the Journal of Organizational Behavior website.

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Journal

Journal of Organizational Behavior

DOI

10.1002/job.2867 

Method of Research

Survey

Subject of Research

People

Article Title

Quiet Workaholics? The Link Between Workaholism and Employee Silence and Moral Voice as Explained by the Social-Cognitive Theory of Morality

Article Publication Date

10-Feb-2025