Over 70% of patients with ovarian cancer are diagnosed at an advanced stage, often presenting with large volumes of ascites. This ascites fluid not only supports the spread of cancer throughout the abdominal cavity but also significantly impairs the body’s immune defences. Understanding how ascites affects the immune system is important for developing better treatments that use the immune system to fight cancer.

In this recent study, researchers from Trinity College Dublin and University College Dublin explored how ascites disrupts immune cell function, with a particular focus on natural killer (NK) cells and T cells, which are key players in the body’s ability to eliminate tumours.

By analysing the contents of ascites fluid from ovarian cancer patients, the team identified a group of fat molecules called phospholipids as key drivers of this immune dysfunction.

Dr Karen Slattery, Research Fellow in the Trinity Translational Medicine Institute, is the first author of the research article just published in leading international journal Science Immunology. She said: “We found that these lipids interfere with NK cell metabolism and suppress their ability to kill cancer cells. Crucially, we also discovered that blocking the uptake of these phospholipids into NK cells using a specific receptor blocker can restore their anti-tumour activity, which offers a compelling new target for therapeutic intervention.”

“This work adds a critical piece to the puzzle of why ovarian cancer is so aggressive and has such poor outcomes. While the immune system is naturally equipped to detect and destroy cancer cells, this function is switched off in many individuals with ovarian cancer, and we now know that this is in part due to the fat-rich environment created by ascites.”

Prof. Lydia Lynch, formerly based in Trinity and now in Princeton University, is the senior author of the research article. She said: “This study marks a significant advancement in ovarian cancer research, identifying a new mechanism underpinning immune failure and laying the foundation for new therapies that could restore immune function in these patients. By targeting the fat-induced suppression of immune cells, future treatments could empower the body’s own immune defences to fight back and in doing so, improve outcomes for ovarian cancer patients.”

Humans are the only species on earth known to use language. They do this by combining sounds into words and words into sentences, creating infinite meanings. This process is based on linguistic rules that define how the meaning of calls is understood in different sentence structures. For example, the word “ape” can be combined with other words to form compositional sentences that add meaning: “the ape eats” or append meaning: “big ape,” and non-compositional idiomatic sentences that create a completely new meaning: “go ape.” A key component of language is syntax, which determines how the order of words affects meaning, for instance how “go ape” and “ape goes” convey different meanings.

One fundamental question in science is to understand where this extraordinary capacity for language originates from. Researchers often use the comparative approach to trace the evolutionary origins of human language by comparing the vocal production of other animals, particularly primates, with that of humans. Unlike humans, other primates typically rely on single calls (referred to as call types), and while some species combine calls, these combinations are only a few per species and mostly serve to alert others to the presence of predators. This suggests that their communication systems may be too restricted to be a precursor to the complex, open-ended combinatorial system that is human language. However, we may not have a full picture of the linguistic capacities of our closest living relatives, particularly how they might use call combinations to significantly expand their meaning.

Studying the meaning of chimpanzee vocalisations

Researchers from the Max Planck Institutes for Evolutionary Anthropology and for Cognitive and Brain Sciences in Leipzig, Germany, and from the Cognitive Neuroscience Center Marc Jeannerod (CNRS/Université Claude Bernard Lyon 1) and Neuroscience Research Center (CNRS/Inserm/Université Claude Bernard Lyon 1) in Lyon, France recorded thousands of vocalisations from three groups of wild chimpanzees in the Taï National Park in Ivory Coast. They examined how the meanings of 12 different chimpanzee calls changed when they were combined into two-call combinations. “Generating new or combined meanings by combining words is a hallmark of human language, and it is crucial to investigate whether a similar capacity exists in our closest living relatives, chimpanzees and bonobos, in order to decipher the origins of human language,” says Catherine Crockford, senior author of the study. “Recording chimpanzee vocalisations over several years in their natural environment is essential in order to document their full communicative capabilities, a task that is becoming increasingly challenging due to growing human threats to wild chimpanzee populations,” says Roman Wittig, co-author of the study and director of the Taï Chimpanzee Project.

Chimpanzees’ complex communication system

The study reveals four ways in which chimpanzees alter meanings when combining single calls into 16 different two-call combinations, analogous to the key linguistic principles in human language. Chimpanzees used compositional combinations that added meaning (e.g., A = feeding, B = resting, AB = feeding + resting) and clarified meaning (e.g., A = feeding or travelling, B = aggression, AB = travelling). They also used non-compositional idiomatic combinations that created entirely new meanings (e.g., A = resting, B = affiliation, AB = nesting). Crucially, unlike previous studies which have mostly reported call combinations in limited situations such as predator encounters, the chimpanzees in this study expanded their meanings through the versatile combination of most of their single calls into a large diversity of call combinations used in a wide range of contexts.

“Our findings suggest a highly generative vocal communication system, unprecedented in the animal kingdom, which echoes recent findings in bonobos suggesting that complex combinatorial capacities were already present in the common ancestor of humans and these two great ape species,” says Cédric Girard-Buttoz, first author on the study. He adds: “This changes the views of the last century which considered communication in the great apes to be fixed and linked to emotional states, and therefore unable to tell us anything about the evolution of language. Instead, we see clear indications here that most call types in the repertoire can shift or combine their meaning when combined with other call types. The complexity of this system suggests either that there is indeed something special about hominid communication — that complex communication was already emerging in our last common ancestor, shared with our closest living relatives — or that we have underestimated the complexity of communication in other animals as well, which requires further study.”

The research team published their findings in the American Journal of Botany.

The fossils, at least two million years old, represent the first direct evidence of an endangered tropical tree species in the fossil record. The research study, conducted in collaboration with the University of Brunei among other international partners, identified fossilized leaves of Dryobalanops rappa, known locally as the Kapur Paya. It is a towering dipterocarp tree that still exists today but is endangered and found in the carbon-rich peatlands of Borneo, including Brunei.

“This discovery provides a rare window into the ancient history of Asia’s wet tropical forests,” said Tengxiang Wang, a doctoral student in the College of Earth and Mineral Sciences at Penn State and lead author on the paper. “We now have fossil proof that this magnificent tree species has been a dominant part of Borneo’s forests for millions of years, emphasizing its ecological importance and the need to protect its remaining habitats.”

Until now, the fossil record of Asia’s wet tropical forests has been surprisingly scarce compared to the Amazon and Africa, said Peter Wilf, professor of geosciences at Penn State and co-author.

The team identified the fossils by analyzing microscopic features of the preserved leaf cuticles, which revealed a perfect match with modern Dryobalanops rappa, down to the last cellular detail.

“Our findings highlight that these forests are not just rich in biodiversity today but have been home to iconic tree species for millions of years,” Wang said. “Conserving them is not only about protecting present-day species but also about preserving a legacy of ecological resilience that has withstood millions of years.”

Dipterocarps, the dominant tree family in Asia’s rainforests, are critical for carbon storage and biodiversity. However, the researchers said, they are increasingly threatened by deforestation and habitat destruction. By revealing the deep historical roots of these trees, this discovery adds an important new perspective to conservation efforts.

“The findings add a new dimension to conservation; we are not only protecting modern species but ancient survivors that have been key components of their unique ecosystems for millions of years,” Wang said. “This historical perspective makes both the endangered trees and their habitats even more valuable for conservation. Our study also shows how fossil evidence can strengthen conservation strategies for threatened species and ecosystems based on their historical significance.”

Understanding the history of tropical forests is essential for their conservation, especially as many key species face rapid decline, Wilf said.

“Penn State’s paleobotany group is making exciting fossil discoveries with our international partners in several Southeast Asian countries, illuminating the poorly known history of the region’s magnificent and severely threatened tropical forests,” Wilf said. “Our finding fossils of living, endangered, giant tree species provides a vital historical foundation for conserving tropical Asia’s keystone trees, the rapidly disappearing dipterocarps.”

Two collaborators on the paper are Penn State alumni: Michael Donovan, The Field Museum; and Xiaoyu Zou, University of California San Diego. Additionally, collaborators from other institutions include Antonino Briguglio, Università degli Studi di Genova; László Kocsis, University of Lausanne; and Ferry Silk, Universiti Brunei Darussalam.

The research was supported by the U.S. National Science Foundation, Universiti Brunei Darussalam research grants and a Penn State Institute of Energy and the Environment seed grant.

Hydrogels are gels composed of polymers that can absorb and retain large amounts of water. They are widely used in wound dressings, drug delivery, tissue engineering, soft robotics, soft contact lenses and more.

Gel formation within minutes

Traditional hydrogel manufacturing relies on chemical initiators, some of which can be harmful, particularly in medical applications. Initiators are the chemicals used to trigger chemical chain reactions. The McGill research team, led by Mechanical Engineering Professor Jianyu Li, has developed an alternative method using ultrasound. When applied to a liquid precursor, sound waves create microscopic bubbles that collapse with immense energy, triggering gel formation within minutes.

“The problem we aimed to solve was the reliance on toxic chemical initiators,” said Li. “Our method eliminates these substances, making the process safer for the body and better for the environment.”

This ultrasound-driven technique is dubbed “sonogel.”

“Typical hydrogel synthesis can take hours or even overnight under UV light,” said Li. “With ultrasound, it happens in just five minutes.”

Revolutionizing biomedical applications

One of the most exciting possibilities for this technology is in non-invasive medical treatments. Because ultrasound waves can penetrate deep into tissues, this method could enable in-body hydrogel formation without surgery.

“Imagine injecting a liquid precursor and using ultrasound to solidify it precisely where needed,” said Li. “This could be a game-changer for treating tissue damage and regenerative medicine. Further refinement, we can unlock new possibilities for safer, greener material production.”

The technique also opens the door to ultrasound-based 3D bioprinting. Instead of relying on light or heat, researchers could use sound waves to precisely “print” hydrogel structures.

“By leveraging high-intensity focused ultrasound, we can shape and build hydrogels with remarkable precision,” said Jean Provost, one of co-authors of the study and assistant professor of engineering physics at Polytechnique Montréal.

Published in PNAS Nexus, the study is the first to estimate the scale of global river contamination from human antibiotics use. Researchers calculated that about 8,500 tonnes of antibiotics — nearly one-third of what people consume annually — end up in river systems around the world each year even after in many cases passing through wastewater systems.

“While the amounts of residues from individual antibiotics translate into only very small concentrations in most rivers, which makes them very difficult to detect, the chronic and cumulative environmental exposure to these substances can still pose a risk to human health and aquatic ecosystems,” said Heloisa Ehalt Macedo, a postdoctoral fellow in geography at McGill and lead author of the study.

The research team used a global model validated by field data from nearly 900 river locations. They found that amoxicillin, the world’s most-used antibiotic, is the most likely to be present at risky levels, especially in Southeast Asia, where rising use and limited wastewater treatment amplify the problem.

“This study is not intended to warn about the use of antibiotics — we need antibiotics for global health treatments — but our results indicate that there may be unintended effects on aquatic environments and antibiotic resistance, which calls for mitigation and management strategies to avoid or reduce their implications,” said Bernhard Lehner, a professor in global hydrology in McGill’s Department of Geography and co-author of the study.

The findings are especially notable because the study did not consider antibiotics from livestock or pharmaceutical factories, both of which are major contributors to environmental contamination.

“Our results show that antibiotic pollution in rivers arising from human consumption alone is a critical issue, which would likely be exacerbated by veterinarian or industry sources of related compounds” said Jim Nicell, an environmental engineering professor at McGill and co-author of the study. “Monitoring programs to detect antibiotic or other chemical contamination of waterways are therefore needed, especially in areas that our model predicts to be at risk.”

Most biochemistry labs that study DNA isolate it within a water-based solution that allows scientists to manipulate DNA without interacting with other molecules. They also tend to use heat to separate strands, heating the DNA to over 150 degrees Fahrenheit, a temperature a cell would never naturally reach. By contrast, in a living cell DNA lives in a very crowded environment, and special proteins attach to DNA to mechanically unwind the double helix and then pry it apart.

“The interior of the cell is super crowded with molecules, and most biochemistry experiments are super uncrowded,” said Northwestern professor John Marko. “You can think of extra molecules as billiard balls. They’re pounding against the DNA double helix and keeping it from opening.”

Marko, a professor of molecular biosciences as well as physics in Northwestern’s Weinberg College of Arts and Sciences, led the research along with Northwestern post-doctoral researcher Parth Desai. In Marko’s lab, for their experiments, he and Desai use microscopic magnetic tweezers to separate DNA and then carefully attach strands of it to surfaces on one end, and tiny magnetic particles on the other, then conduct high-tech imaging. The technology has been around for 25 years, and Marko was one of the first researchers theorizing about and then using it.

Marko and Desai wrote the paper that not only identifies but quantifies the amount of stress imposed by crowding, that will be published on June 17 in the Biophysical Journal.

Desai introduced three types of molecules to the solution holding DNA to mimic proteins and investigated interactions among glycerol, ethylene glycol and polyethylene glycol (each approximately the size of one DNA double helix, two or three nanometers).

“We wanted to have a wide variety of molecules where some cause dehydration, destabilizing DNA mechanically, and then others that stabilize DNA,” Desai said. “It’s not exactly analogous to things found in cells, but you could imagine that other competing proteins in cells will have a similar effect. If they’re competing for water, for instance, they would dehydrate DNA, and if they’re not competing for water, they would crowd the DNA and have this entropic effect.”

While fundamental, research like this has “been the basis for many, many, many medical advances,” Marko said, such as deep sequencing of DNA, where scientists can now sequence an entire human genome in under a day. He also thinks their findings may be broadly applicable to other elements of fundamental biochemical processes.

“If this affects DNA strand separation, all protein interactions with DNA are also going to be affected,” Marko said. “For example, the tendency for proteins to stick to specific sites on DNA and to control specific processes — this is also going to be altered by crowding.”

In addition to running more experiments that incorporate multiple crowding agents, the team hopes to move closer to a true representation of a cell, and from there, study how interactions between enzymes and DNA are impacted by crowding.

This work was supported by the National Institutes of Health (grant R01-GM105847) and by subcontract to the University of Massachusetts Center for 3D Structure and Physics of the Genome (under NIH grant UM1-HG011536).

Data centers house and use large computers to run massive amounts of data. Oftentimes, the processors can’t keep up with this workload because it’s taxing to predict and prepare instructions to carry out. This slows the flow of data. Thus, when you type a question into a search engine, the answer generates more slowly or doesn’t provide the information you need.

To remedy this issue, researchers at Texas A&M University developed a new technique called Skia in collaboration with Intel, AheadComputing, and Princeton to help computer processors better predict future instructions and improve computing performance.

The team includes Dr. Paul V. Gratz, a professor in the Department of Electrical and Computer Engineering, Dr. Daniel A. Jiménez, a professor in the Department of Computer Science and Engineering, and Chrysanthos Pepi, a graduate student in the Department of Electrical and Computer Engineering.

“Processing instructions has become a major bottleneck in modern processor design,” Gratz said. “We developed a new technique, Skia, to better predict what’s coming next and alleviate that bottleneck.”

A common problem for modern data center workloads is that the instruction stream — the steps a computer must take for processing — can be too large or difficult to process. Skia, a Greek word for shadow, can not only help better predict future instructions, but based upon that information, it can improve the throughput of instructions on the system. Throughput refers to units of completed processing per units of time.

“Think of throughput in terms of being a server in a restaurant,” Gratz said. “You have lots and lots of jobs to do. How many tasks can you complete, or how many instructions can you execute per unit time? You want high throughput, especially for computing.”

Improving throughput can lead to quicker performance and less power consumption for the data center.

“There are new bottlenecks in data center workloads associated with the instruction footprint and by fixing these, we can make the hardware better mapped and suited to that workload,” Gratz added. “If we make it up to 10% more efficient, a company previously needing to make 100 data centers around the country, now only needs to make 90, which is 10 less data centers. That’s pretty significant. These data centers cost millions of dollars, and they consume roughly the equivalent of the entire output of a power plant.”

In data centers, modern processors improve efficiency by predicting instructions and retrieving them before they’re needed, relying on a system known as Fetch Directed Instruction Prefetching (FDIP). FDIP uses Branch Prediction Unit to anticipate and fetch instructions.

However, as data center applications grow more complex, issues can occur when the Branch Target Buffer (BTB), which helps to monitor and track instructions, faults. This hinders FDIPS’s effectiveness, causing incorrect predictions and cache pollution. Many of these missed branches, termed “Shadow Branches,” exist in previously fetched cache lines but aren’t being used by the current instruction sequence and remain undecoded.

Skia identifies and decodes these shadow branches in unused bytes, storing them in a memory area called the Shadow Branch Buffer, which can be accessed alongside the BTB.

“What makes this technique interesting is that most of the future instructions were already available, and we demonstrate that Skia, with a minimal hardware budget, can make data centers more efficient, nearly twice the performance improvement versus adding the same amount of storage to the existing hardware as we observe,” Pepi said.

Their findings, “Skia: Exposing Shadow Branches,” were published in one of the leading computer architecture conferences, the ACM International Conference on Architectural Support for Programming Languages and Operating Systems. The team also traveled to the Netherlands to present their work to colleagues from around the globe.

Other collaborators on the project include David I. August, a professor in the Department of Computer Science from Princeton University, Krishnam Tibrewala, a graduate student in the Computer Science and Engineering Department at Texas A&M, Gilles Pokam, a senior principal engineer at Intel Corporation, and Bhargav Reddy Godala and Gino Chacon, senior central processing unit architects at AheadComputing.

Funding for this research is administered by the Texas A&M Engineering Experiment Station (TEES), the official research agency for Texas A&M Engineering.

A University of Washington-led team has developed a system, called ProxiCycle, that logs when a passing car comes too close to a cyclist (within four feet). A small, inexpensive sensor plugs into bicycle handlebars and tracks the passes, sending them to the rider’s phone. The team tested the system for two months with 15 cyclists in Seattle and found a significant correlation between the locations of close passes and other indicators of poor safety, such as collisions. Deployed at scale, the system could support mapping or navigating cyclists on safer bike routes through cities.

“Experienced cyclists have this mental map of which streets are safe and which are unsafe, and I wanted to find a simple way to pass that knowledge down to novice cyclists,” said lead author Joseph Breda, a UW doctoral student in the Paul G. Allen School of Computer Science & Engineering. “Cycling is really good for your health and for the environment. Getting more people biking more often is how we reap those rewards and increase safety in numbers for cyclists on the roads.”

The team presented its research Apr. 29 at the ACM CHI Conference on Human Factors in Computing Systems in Yokohama, Japan.

To start, researchers surveyed 389 people in Seattle. Respondents of all cycling experience levels ranked the threat of cars as the factor which most discouraged them from cycling, and said they’d be very likely to use a map that helps navigate for safety. But a key factor preventing this is limited data on road safety.

The team then built a small sensor system that plugs into a bike’s left handlebar. The system, which costs less than $25 to build, consists of a 3D printed plastic casing that houses a pair of sensors and a Bluetooth antenna. The antenna transmits data to the rider’s phone, where the team’s algorithm susses out what’s a passing car rather than a person, or another cyclist, or a tree.

The team validated the system both by testing it in a parking lot, with a car passing at different distances, and with seven cyclists riding through Seattle with GoPro cameras on their handlebars. Researchers watched the footage from these rides and compared this to the sensor output.

The team then recruited 15 cyclists through the newsletter of Seattle Neighborhood Greenways, a local advocacy group. Each got a ProxiCycle sensor, a custom Android application and instructions. The cyclists took 240 bike rides over two months and recorded 2,050 close passes. Researchers then compared the locations of close passes with riders’ perceived safety at different locations in the city — which they measured by showing cyclists images of locations and having them rate how safe they felt at those locations (referred to as “perceived safety”) — and with the locations of known automobile-to-bike collisions in the last five years.

The team found a significant correlation between close passes and both other indicators of cycling risk. They also found that this measure of close passes was a better indicator of actual safety than the surveyed perceived safety, which is the current standard used by policymakers to study safety when collisions aren’t enough.

In the future, researchers hope to scale the study up and potentially account for other risk factors, such as cyclists being hit by opening car doors, and deploy ProxiCylce in other cities. With enough data, existing bike mapping apps, such as Google Maps or Strava, might include safer route suggestions for cyclists.

Some of those routes involve only minor adjustments.

“One study participant, who was living down by Seattle Center, was biking down Mercer all the time,” Breda said. “It’s this busy, multi-lane road. But just before the study, they found out that there’s a great bike lane on a quieter street, just one block north.”

Keyu Chen, an applied science lead at Gridware, and Thomas Ploetz, a professor at Georgia Institute of Technology, are also co-authors on this paper. Shwetak Patel, a UW professor in the Allen School, is the senior author.