For about fifty years, scientists have puzzled over another related mystery. Most large galaxies near our own, aside from Andromeda, appear to be moving away from us rather than being pulled inward by gravity. This seems surprising because these galaxies reside near the Local Group (the Milky Way, the Andromeda Galaxy and dozens of smaller galaxies), whose combined mass should exert a noticeable gravitational influence.

A Giant Cosmic Sheet Around the Local Group

An international research team led by PhD graduate Ewoud Wempe of the Kapteyn Institute in Groningen believes it has found the explanation. Using advanced computer simulations, the researchers discovered that the matter surrounding the Local Group is arranged in a broad, flattened structure that stretches tens of millions of light-years across. This structure includes not only ordinary matter but also the invisible dark matter that surrounds galaxies. Above and below this flattened region lie enormous empty areas known as cosmic voids.

The simulations show that this arrangement of matter can accurately reproduce both the positions and speeds of the galaxies observed around us. In other words, the computer model successfully recreates the same patterns astronomers see in the real universe.

Creating a Virtual Twin of Our Cosmic Neighborhood

To build their model, the scientists began with conditions from the early universe. They used measurements of the cosmic microwave background to estimate how matter was distributed shortly after the Big Bang. A powerful computer then evolved this early universe forward in time, eventually producing a system that matches the present day Local Group.

The resulting simulations replicate the masses, locations, and motions of the Milky Way and Andromeda, as well as the positions and velocities of 31 galaxies just outside the Local Group. Because the model so closely resembles our surroundings, researchers describe it as a “virtual twin” of our cosmic environment.

When the model includes the flat distribution of matter, the surrounding galaxies move away from us at speeds similar to those actually observed. Despite the gravitational pull of the Local Group, galaxies within the plane are influenced by additional mass spread throughout that same plane. This distant mass counterbalances the Local Group’s gravity. Meanwhile, regions outside the plane contain very few galaxies, which explains why we do not see objects falling toward us from those directions.

A Longstanding Puzzle Finally Explained

According to lead researcher Ewoud Wempe, the study represents the first detailed attempt to determine the distribution and motion of dark matter in the area around the Milky Way and Andromeda. “We are exploring all possible local configurations of the early universe that ultimately could lead to the Local Group. It is great that we now have a model that is consistent with the current cosmological model on the one hand, and with the dynamics of our local environment on the other.”

Astronomer Amina Helmi also welcomed the findings, noting that the problem has challenged researchers for decades. “I am excited to see that, based purely on the motions of galaxies, we can determine a mass distribution that corresponds to the positions of galaxies within and just outside the Local Group.”

The finding could open new paths for designing technologies that capture sunlight more efficiently and convert it into electricity.

In laboratory experiments tracking events lasting just 18 femtoseconds — less than 20 quadrillionths of a second — researchers at the University of Cambridge observed electric charge separating during a single molecular vibration.

“We deliberately designed a system that, according to conventional theory, should not have transferred charge this fast,” said Dr. Pratyush Ghosh, Research Fellow, at St John’s College, Cambridge, and first author of the study. “By conventional design rules, this system should have been slow and that’s what makes the result so striking.

“Instead of drifting randomly, the electron is launched in one coherent burst. The vibration acts like a molecular catapult. The vibrations don’t just accompany the process, they actively drive it.”

Watching Electrons Move on the Timescale of Atoms

A femtosecond is one quadrillionth of a second — one second holds about eight times more femtoseconds than all the hours that have passed since the universe began. At this incredibly small timescale, atoms inside molecules are constantly vibrating.

The researchers observed electrons moving between materials at essentially the same pace as those atomic motions. As Ghosh explained, “We’re effectively watching electrons migrate on the same clock as the atoms themselves.”

The research, published in Nature Communications March 5, 2026, challenges long standing design assumptions in solar energy science. Until now, scientists generally believed that ultrafast charge transfer required large energy differences between materials and strong electronic coupling. Those conditions can reduce efficiency by limiting voltage and increasing energy loss.

How Light Creates Energy in Solar Materials

When light strikes many carbon based materials, it creates a tightly bound packet of energy called an exciton — a paired electron and hole. For devices such as solar cells, photodetectors and photocatalytic systems to function effectively, this pair must separate quickly into free charges.

The faster the split occurs, the less energy is wasted. This ultrafast separation plays a critical role in determining how efficiently solar panels and other light harvesting technologies convert sunlight into usable power.

To investigate whether this trade off was unavoidable, the Cambridge researchers intentionally created what they expected to be a poorly performing system. They placed a polymer donor next to a non fullerene acceptor with almost no energy difference and only weak interaction — conditions that should have significantly slowed charge transfer.

Instead, the electron crossed the interface in just 18 femtoseconds. That speed is faster than many previously studied organic systems and matches the natural rhythm of atomic motion. “Seeing it happen on this timescale within a single molecular vibration is extraordinary,” said Dr. Ghosh.

Molecular Vibrations Drive Ultrafast Electron Motion

Ultrafast laser experiments helped reveal the mechanism behind this unexpected result. When the polymer absorbs light, it begins vibrating in specific high frequency patterns.

These vibrations mix electronic states and effectively push the electron across the boundary, creating a directional, ballistic motion instead of slow and random diffusion.

Once the electron reaches the acceptor molecule, it sets off a new coherent vibration. This distinctive signal is rarely observed in organic materials and indicates how quickly the transfer occurs. “That coherent vibration is a clear fingerprint of how fast and how cleanly the transfer occurs.

“Our results show that the ultimate speed of charge separation isn’t determined only by static electronic structure,” said Dr. Ghosh. “It depends on how molecules vibrate. That gives us a new design principle. In a way, this gives us a new rulebook. Instead of fighting molecular vibrations, we can learn how to use the right ones.”

Implications for Solar Energy and Light Harvesting

The discovery suggests a new strategy for designing more efficient light harvesting technologies. Ultrafast charge separation is fundamental to systems such as organic solar cells, photodetectors and photocatalytic devices that can produce clean hydrogen fuel. Similar processes also occur naturally during photosynthesis.

Professor Akshay Rao, Professor of Physics at the Cavendish Laboratory and former St John’s College Research Associate, who was a co author of the study, said: “Instead of trying to suppress molecular motion, we can now design materials that use it — turning vibrations from a limitation into a tool.”

The project involved scientists from the Cavendish Laboratory and the Yusuf Hamied Department of Chemistry at the University of Cambridge, including Dr. Rakesh Arul, St John’s College Research Fellow. Collaborators in Italy, Sweden, the United States, Poland and Belgium also contributed to the research.

The study, partly funded by the National Institutes of Health, was published March 4 in Science Translational Medicine. It marks the first time that this type of DNA fragmentation analysis, known as fragmentome technology, has been systematically applied to detecting chronic diseases unrelated to cancer. Previously, the approach had mainly been investigated as a method for finding cancer.

Genome Wide DNA Fragment Patterns Reveal Disease Signals

Liquid biopsies that measure cfDNA have already shown promise for identifying cancer. However, scientists have not widely explored their potential for diagnosing other illnesses. In this new research, investigators performed whole genome sequencing on cfDNA samples from 1,576 individuals with liver disease and additional medical conditions. By examining DNA fragments across the entire genome, they searched for patterns that might signal disease.

The team analyzed both the size of DNA fragments and their distribution throughout the genome, including repetitive DNA regions that have rarely been studied. Each analysis included about 40 million fragments spanning thousands of genomic regions, producing an enormous dataset compared with most liquid biopsy tests.

Machine learning algorithms processed this information to identify fragmentation patterns linked to disease. Using these patterns, researchers created a classification system that detected early liver disease, advanced fibrosis and cirrhosis with high sensitivity.

“This builds directly on our earlier fragmentome work in cancer, but now using AI and genome-wide fragmentation profiles of cell-free DNA to focus on chronic diseases,” says Victor Velculescu, M.D., Ph.D., co-director of the cancer genetics and epigenetics program at the Johns Hopkins Kimmel Cancer Center and co-senior author of the study. “For many of these illnesses, early detection could make a profound difference, and liver fibrosis and cirrhosis are important examples. Liver fibrosis is reversible in early its stages, but if left undetected, it can progress to cirrhosis and ultimately increase the risk of liver cancer.”

Why DNA Fragment Analysis Is Different

Unlike many liquid biopsy methods that search for specific cancer related gene mutations, the fragmentome approach focuses on how DNA fragments are cut, packaged and distributed throughout the genome. According to the researchers, this broader view makes the method applicable to conditions beyond cancer, including diseases that can eventually raise cancer risk. The study was also co led by Robert Scharpf, Ph.D., professor of oncology, and Jill Phallen, Ph.D., assistant professor of oncology.

“The fact that we are not looking for individual mutations is what makes this study so powerful,” says first author Akshaya Annapragada, an M.D./Ph.D. student in the Velculescu lab. “We are analyzing the entire fragmentome, which contains a tremendous amount of information about a person’s physiologic state. The scale of these data, coupled with machine learning, enables development of specific classifiers for many different health conditions.”

Early Detection Could Benefit Millions at Risk

Velculescu notes that roughly 100 million people in the United States have liver conditions that increase their risk of cirrhosis and liver cancer. Current blood based tests for fibrosis often lack sensitivity, especially in early stages of disease. Standard blood markers typically fail to detect early fibrosis and identify cirrhosis only about half the time. Imaging techniques such as specialized ultrasound or magnetic resonance scans can help, but these tools require equipment that is not always available.

“Many individuals at risk don’t know they have liver disease,” Velculescu says. “If we can intervene earlier — before fibrosis progresses to cirrhosis or cancer — the impact could be substantial.”

He adds that identifying these precursor conditions early may allow doctors to treat underlying diseases sooner and potentially prevent cancer from developing.

Study Origins and the Fragmentome Comorbidity Index

The research grew out of a 2023 Cancer Discovery study led by Velculescu that focused on the fragmentome of liver cancer. While studying patients with liver tumors, the scientists noticed that some individuals with fibrosis or cirrhosis showed mostly normal fragmentation profiles but contained subtle DNA signals linked to disease. This observation prompted the team to examine the fragmentome patterns associated specifically with liver fibrosis and cirrhosis.

In another analysis involving 570 people with suspected serious illness, researchers created a fragmentation comorbidity index. This measure distinguished individuals with high and low Charlson Comorbidity Index scores, a widely used metric that estimates how additional health conditions affect a person’s risk of death. The fragmentome based index predicted overall survival independently and in some cases proved more specific than traditional inflammatory markers. Certain fragmentation signatures also appeared to be associated with poorer clinical outcomes.

“The fragmentome can serve as a foundation for building different classifiers for different diseases, and importantly, these classifiers are disease-specific and do not cross-react,” Annapragada says. “A liver fibrosis classifier is distinct from a cancer classifier. This is a unique, disease-specific test built from the same underlying platform.”

Potential to Detect Other Chronic Diseases

The study also included people at elevated risk for a range of medical conditions. Researchers observed fragmentome signals linked to cardiovascular, inflammatory and neurodegenerative disorders. However, the study population did not include enough cases to build separate disease classifiers for each of these conditions. Instead, the findings suggest that the technology may eventually have wider medical applications, which researchers plan to investigate in future work.

The liver fibrosis assay described in the study remains a prototype and has not yet been introduced as a clinical test. The team’s next steps involve refining and validating the classifier for liver disease and exploring fragmentome signatures connected to other chronic illnesses.

Researchers and Funding

Along with Velculescu, Annapragada, Scharpf and Phallen, the research team included Zachariah Foda, Hope Orjuela, Carter Norton, Shashikant Koul, Noushin Niknafs, Sarah Short, Keerti Boyapati, Adrianna Bartolomucci, Dimitrios Mathios, Michael Noe, Chris Cherry, Jacob Carey, Alessandro Leal, Bryan Chesnick, Nic Dracopoli, Jamie Medina, Nicholas Vulpescu, Daniel Bruhm, Sarah Bacus, Vilmos Adleff, Amy Kim, Stephen Baylin, Gregory Kirk, Andrei Sorop, Razvan Iacob, Speranta Iacob, Liana Gheorghe, Simona Dima, Katherine McGlynn, Manuel Ramirez-Zea, Claus Feltoft, Julia Johansen and John Groopman.

Funding for the research came in part from the Dr. Miriam and Sheldon G. Adelson Medical Research Foundation, SU2C in-Time Lung Cancer Interception Dream Team Grant, Stand Up to Cancer-Dutch Cancer Society International Translational Cancer Research Dream Team Grant, the Gray Foundation, The Honorable Tina Brozman Foundation, the Commonwealth Foundation, the Mark Foundation for Cancer Research, the Danaher Foundation and ARCS Metro Washington Chapter, the Family of Dan Y. Zhang AACR Scholar in Training Award, the Cole Foundation and National Institutes of Health grants CA121113, CA006973, CA233259, CA062924, CA271896, T32GM136577, T32GM148383 and DA036297.

Until now, scientists have not fully understood how these two types of guidance work together. An international research team has discovered that the stiffness of brain tissue can control the production of important signalling molecules. The findings, published in Nature Materials, reveal a direct link between mechanical forces and chemical signalling in the brain. This insight may also help researchers better understand how other organs develop and could eventually inspire new medical strategies.

Chemical Signals and Physical Cues Work Together

For many years, scientists have known that chemical signals guide how tissues grow and organize. Gradients of signalling molecules act like directional cues, helping cells move and develop in the correct locations.

More recent studies have shown that physical factors such as tissue stiffness also influence how cells behave. However, the relationship between these mechanical cues and chemical signals has remained unclear. Understanding how the two interact is critical for explaining how complex tissues such as the brain form during development.

Study Reveals Tissue Stiffness Controls Key Brain Signals

Researchers from the Max-Planck-Zentrum für Physik und Medizin (MPZPM), the Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), and the University of Cambridge investigated this question using Xenopus laevis (African clawed frogs), a widely used model organism in developmental biology. Their experiments showed that tissue stiffness can regulate the production of important chemical guidance cues.

This process is controlled by a mechanosensitive protein called Piezo1. The team, led by Prof. Kristian Franze, found that when tissue stiffness increased, cells began producing signalling molecules that are normally absent from those areas. One example is the guidance molecule Semaphorin 3A. Notably, this response only occurred when Piezo1 levels were sufficiently high.

“We didn’t expect Piezo1 to act as both a force sensor and a sculptor of the chemical landscape in the brain,” said study co-lead Eva Pillai, a postdoctoral researcher at the European Molecular Biology Laboratory (EMBL). “It not only detects mechanical forces — it helps shape the chemical signals that guide how neurons grow. This kind of connection between the brain’s physical and chemical worlds gives us a whole new way of thinking about how it develops.”

Piezo1 Also Helps Maintain Tissue Structure

The researchers also discovered that Piezo1 influences the physical stability of brain tissue itself. When the amount of Piezo1 is reduced, levels of important cell adhesion proteins including NCAM1 and N-cadherin drop. These proteins are crucial for maintaining cell-cell contacts — which glue cells together.

“What’s exciting is that Piezo1 doesn’t just help neurons sense their environment — it helps build it,” said Sudipta Mukherjee, study co-lead and postdoctoral researcher at FAU and MPZPM. He and Pillai were both doctoral students at the University of Cambridge, where the project was initiated. “By regulating the levels of these adhesion proteins, Piezo1 keeps cells well connected, which is essential for a stable tissue architecture. The stability of the enviroment in turn, influences the chemical environment.”

The results indicate that Piezo1 performs two important roles. It acts as a sensor that converts mechanical signals from the surrounding environment into cellular responses. At the same time, it functions as a modulator that helps organize the mechanical properties of the tissue itself.

Implications for Development and Disease

These findings could have wide ranging significance for developmental biology and medical research. Errors in neuron growth are associated with congenital and neurodevelopmental disorders. In addition, tissue stiffness has been linked to diseases such as cancer.

By demonstrating that mechanical forces can shape chemical signalling, the study provides new insight into how tissues form and function. It also suggests new directions for research into disease and potential treatments.

“Our work shows that the brain’s mechanical environment is not just a backdrop — it is an active director of development,” said senior author Kristian Franze. “It regulates cell function not only directly, but also indirectly by modulating the chemical landscape. This study may lead to a paradigm shift in how we think about chemical signals, with implications for many processes from early embryonic development to regeneration and disease.”

The researchers also found that tissue stiffness can influence chemical signalling across long distances, affecting the behavior of cells far from where the mechanical force originates. Overall, the study highlights mechanical forces as a powerful regulator of development and organ function.

The research team examined how droughts begin in different parts of the world and whether they occur at roughly the same time. The study was led by Dr. Udit Bhatia of IITGN, with contributions from researchers at IITGN and the Helmholtz Centre for Environmental Research — UFZ in Leipzig, Germany.

“We treated drought onsets as events in a global network. If two distant regions entered drought within a short time window, they were considered synchronized,” explained Dr. Bhatia, the lead author and principal investigator of the Machine Intelligence and Resilience Lab and the AI Resilience and Command (ARC) Centre at IITGN.

Global “Drought Hubs” and Crop Risk

By charting thousands of these drought connections, researchers identified several regions that often act as major centers of drought activity. These so called “drought hubs” include Australia, South America, southern Africa, and parts of North America.

The team also compared climate patterns with historical agricultural data to understand how moderate drought conditions influence food production. They analyzed crop yields for wheat, rice, maize, and soybean across multiple regions.

“In many major agricultural regions, when moderate drought occurs, the probability of crop failure rises sharply — often above 25%, and in some areas, above 40-50% for crops like maize and soybean,” said Hemant Poonia, an AI Scientist at IITGN who completed his undergraduate and postgraduate degrees in Civil Engineering from the Institute.

Although such risks could become severe if drought affected many farming regions at the same time, the researchers found that natural climate processes help prevent that scenario. Changes in sea surface temperatures, particularly in the Pacific Ocean, limit how widely drought conditions spread across continents.

El Niño and La Niña Shape Global Drought Patterns

One of the strongest influences on these shifting patterns is the El Niño-Southern Oscillation, a natural warming and cooling cycle in the Pacific Ocean that affects rainfall around the world.

During El Niño phases, Australia often becomes a major drought hub, while other regions respond in different ways. When La Niña conditions develop, drought patterns shift again and tend to spread across a wider range of locations.

“These ocean-driven swings create a patchwork of regional responses, limiting the emergence of a single, global drought covering many continents at once,” explained co-author Danish Mansoor Tantary, a former IITGN master’s student who is now pursuing his PhD at Northeastern University (USA).

Rainfall and Rising Temperatures Both Affect Drought Severity

Researchers also investigated how rainfall and temperature together influence the intensity of drought. Their analysis suggests that precipitation changes account for about two thirds of long term shifts in drought severity over recent decades. The remaining third is linked to increasing evaporative demand caused by rising temperatures.

“Rainfall remains the dominant driver globally, especially in regions like Australia and South America, but the influence of temperature is clearly growing in several mid-latitude regions, such as Europe and Asia,” said Dr. Rohini Kumar, the corresponding author and senior scientist at the Helmholtz Centre for Environmental Research, whose work focuses on interactions between water, land, and climate systems.

Early Warning Signals for Global Food Security

The findings show how large scale, data driven analysis of climate patterns can help protect global food supplies. By studying drought as part of an interconnected planetary system rather than as isolated weather events, scientists can identify potential early warning regions before local droughts expand into broader crises.

Prof Vimal Mishra, a leading water and climate expert at IITGN and recipient of the Shanti Swarup Bhatnagar Prize, India’s highest multidisciplinary science award, emphasized the broader implications.

“These findings underline the importance of international trade, storage, and flexible policies. Because droughts do not hit all regions at the same time, smart planning can use this natural diversity to buffer global food supplies.”

Using Climate Insights to Reduce Future Risk

Dr. Bhatia noted that the research highlights how understanding climate systems can guide better policy decisions in a warming world.

“Our research highlights that we are not helpless in the face of a warming planet,” said Dr. Bhatia. “By understanding the delicate balance between oceans, rainfall, and temperatures, policymakers can focus their resources on specific drought hubs and create pipelines to stabilize the global market before crop failures in one region trigger price spikes in another.”

The authors acknowledged support from the Anusandhan National Research Foundation (SERB) Network of Networks grant, Projekt DEAL, and AI Centre of Excellence (AICoE) in sustainable cities.

A new and far more comprehensive analysis now challenges that timeline. By examining 17 tyrannosaur specimens ranging from young juveniles to enormous adults, researchers determined that the famous predator likely continued growing for around 40 years before reaching its maximum weight of roughly eight tons.

The study, published in the journal PeerJ, represents the most detailed reconstruction of the life history of T. rex so far. Researchers combined advanced statistical modeling with microscopic examination of bone slices. Using a specialized lighting technique, they were able to detect previously overlooked growth rings. These hidden markers allowed the team to build a more complete picture of tyrannosaur growth patterns. The findings also hint that some fossils previously classified as T. rex could actually belong to different species or represent other biological differences.

Reconstructing the Life History of Tyrannosaurus Rex

“This is the largest data set ever assembled for Tyrannosaurus rex,” says Holly Woodward, a professor of anatomy at Oklahoma State University who led the research effort. “Examining the growth rings preserved in the fossilized bones allowed us to reconstruct the animals’ year-by-year growth histories.”

However, the fossil record does not preserve the entire lifespan of an individual animal. Unlike the full sequence of rings visible in a tree trunk, a cross section of T. rex bone typically captures only the final 10 to 20 years of the dinosaur’s life.

To fill those gaps, the researchers developed a new analytical method. By combining growth information from multiple specimens of different ages, they created a composite growth curve for the species.

“We came up with a new statistical approach that stitches together growth records from different specimens to estimate the growth trajectory of T. rex across all stages of life in greater detail than any previous study,” explains Nathan Myhrvold, a mathematician and paleobiologist at Intellectual Ventures who led the statistical analysis. “The composite growth curve provides a much more realistic view of how Tyrannosaurus grew and how much they varied in size.”

A Longer Growth Period for the King of Dinosaurs

The results suggest that Tyrannosaurus did not rapidly reach adulthood. Instead, the dinosaurs appear to have grown gradually over several decades.

Rather than maturing quickly, T. rex experienced a prolonged growth phase lasting roughly four decades. According to the researchers, this extended development may have played an important ecological role.

“A four-decade growth phase may have allowed younger tyrannosaurs to fill a variety of ecological roles within their environments,” says coauthor Jack Horner of Chapman University. “That could be one factor that allowed them to dominate the end of the Cretaceous Period as apex carnivores.”

Could Some Famous Fossils Belong to Other Species

Although Tyrannosaurus rex is the best known species in this group of dinosaurs, scientists continue to debate whether some fossils assigned to T. rex actually belong to closely related species.

Some researchers have proposed that certain smaller fossils represent a distinct species called Nanotyrannus rather than young Tyrannosaurus individuals. Others have suggested that even the largest specimens might belong to two or three separate species.

These ideas remain controversial within the scientific community.

To explore the issue further, the new study examined 17 specimens within what researchers describe as the “Tyrannosaurus rex species complex.” This term acknowledges the possibility that the fossils may represent multiple related species or subspecies.

One notable result involves two well known fossils nicknamed “Jane” and “Petey.” Their growth patterns differ significantly from those of the other specimens in the dataset. While growth data alone cannot prove that they represent separate species, the difference raises intriguing questions. A separate recent analysis by Zanno and Napoli reached a similar conclusion using different techniques, identifying Jane and Petey as belonging to two distinct species of Nanotyrannus.

New Imaging Technique Reveals Hidden Growth Rings

Another key finding involves the discovery of a previously unrecognized type of growth ring in dinosaur bone. Woodward, Myhrvold, and Horner found that circularly polarized and cross-polarized light can reveal growth features that are difficult to detect with standard methods.

This approach helps clarify puzzling growth patterns seen in some specimens. The researchers supported the finding with strong statistical evidence, suggesting that traditional techniques for counting dinosaur growth rings may sometimes overlook important details.

“Interpreting multiple closely spaced growth marks is tricky,” Myhrvold says. “We found strong evidence that the protocols typically used in growth studies may need to be revised.”

A Clearer Picture of Tyrannosaurus Life

More than a century after Tyrannosaurus rex was first discovered, the species continues to surprise scientists. By combining a larger fossil sample, new analytical tools, and improved imaging methods, the research offers a clearer understanding of how these iconic predators grew and developed.

The results provide a more complete portrait of Tyrannosaurus rex as a living animal, tracing its journey from young dinosaur to one of the largest land predators in Earth’s history.