Some of the most common symptoms of the ‘long cold’ included coughing, stomach pain, and diarrhea more than 4 weeks after the initial infection. While the severity of an illness appears to be a key driver of risk of long-term symptoms, more research is being carried out to establish why some people suffer extended symptoms while others do not.

The findings suggest that there may be long-lasting health impacts following non-COVID acute respiratory infections such as colds, influenza, or pneumonia, that are currently going unrecognised. However, the researchers do not yet have evidence suggesting that the symptoms have the same severity or duration as long Covid.

The research, funded by Barts Charity, compared the prevalence and severity of long-term symptoms after an episode of COVID-19 vs. an episode of another acute respiratory infection that tested negative for COVID-19. Those recovering from COVID-19 were more likely to experience light-headedness or dizziness and problems with taste and smell compared to those who had a non-COVID-19 respiratory infection.

While long Covid is now a recognised condition, there have been few studies comparing long-term symptoms following SARS-CoV-2 coronavirus infection vs. other respiratory infections.

The study is the latest output from COVIDENCE UK, Queen Mary University of London’s national study of COVID-19, launched back in 2020 and still in follow-up, with over 19,000 participants enrolled. This study analysed data from 10,171 UK adults, with responses collected via questionnaires and statistical analysis carried out to identify symptom clusters.

Giulia Vivaldi, researcher on COVIDENCE UK from Queen Mary University of London and the lead author of the study, said: “Our findings shine a light not only on the impact of long Covid on people’s lives, but also other respiratory infections. A lack of awareness — or even the lack of a common term — prevents both reporting and diagnosis of these conditions.

“As research into long Covid continues, we need to take the opportunity to investigate and consider the lasting effects of other acute respiratory infections.

“These ‘long’ infections are so difficult to diagnose and treat primarily because of a lack of diagnostic tests and there being so many possible symptoms. There have been more than 200 investigated for long Covid alone.”

Professor Adrian Martineau, Chief Investigator of COVIDENCE UK and Clinical Professor of Respiratory Infection and Immunity at Queen Mary University of London, said: “Our findings may chime with the experience of people who have struggled with prolonged symptoms after having a respiratory infection despite testing negative for COVID-19 on a nose or throat swab.

“Ongoing research into the long-term effects of COVID-19 and other acute respiratory infections is important because it can help us to get to the root of why some people experience more prolonged symptoms than others. Ultimately this could help us to identify the most appropriate form of treatment and care for affected people.”

Victoria King, Director of Funding and Impact at Barts Charity said: “Barts Charity swiftly supported COVIDENCE UK in response to the outbreak of COVID-19 to help inform of its risk factors and impacts. These findings highlight not only the long-term symptoms experienced by people after Covid infection, but by people after other acute respiratory infections as well. As we learn more about long Covid symptoms and their possible treatments, studies like this help to build greater awareness around other prolonged respiratory infections that may be going unrecognised.”

Editor’s Note: See also “You’ve heard of long COVID, but did you know there might also be a long cold?” by Giulia Vivaldi, Queen Mary University of London, in The Conversation: https://theconversation.com/youve-heard-of-long-covid-but-did-you-know-there-might-also-be-a-long-cold-214995

Details of past climate conditions are revealed to researchers not only by sediment samples from the ocean floor, but also by the surface of the seafloor, which is exposed to currents that are constantly altering it. Deposits shaped by near-bottom currents are called contourites. These sediment deposits contain information about past ocean conditions as well as clues to climate. Contourites are often found on continental slopes or around deep-sea mountains. But they can be found in any environment where strong currents occur near the seafloor. The mechanisms that control them are not yet well understood. Experiments in flume tanks will help to change this through the depiction of deposition in future models.

Detailed observations of changes in flume-tank experiments

Henriette Wilckens, first author of the newly published study, created a replica of the continental slope in a special flume tank at the University of Utrecht (Netherlands). Currents and sediment input in the flume tank were simulated using pumps and monitored with a current meter. The formation and development of the sediment deposits were measured with a laser scanner. All the data obtained were compared to measurements in natural ocean systems in order to validate the results of the experiments.

“The internal sediment architecture of contourites can be observed from seismic data, but in order to unlock information about the past ocean currents we need a better understanding of how they developed and the factors that influence the contourite systems,” explains Wilckens. While it is impossible to directly see how natural marine systems that developed over time periods of thousands to millions of years started to form on the seafloor, scientists can employ flume-tank experiments to directly observe detailed changes of the seafloor morphology and control their related current velocities.

Huge application potential of the models

“Our experiment can also be applied to the entire deep sea and even to lakes,” says Henriette Wilckens, meaning anywhere in the deep sea where there is a slope, terraces, deep-sea mountains or, for example, cold-water coral mounds.

It is also conceivable that the models could be applied, for example, to improve predictions of how currents transport microplastic particles or other pollutants in the ocean. “The potential for its application,” says Wilckens, “is immense. The system must first be understood before it is possible to derive information from it.”

Opening a new branch of research

“This research work is an important step toward a better understanding of the ways in which ocean currents control the deposition of particles in the seafloor, which has important implications for paleoceanographic reconstructions and benthic ecology. This introduces a new branch of research that will probably lead to even more exciting discoveries,” according to Elda Miramontes, co-author of the study and head of the “Sedimentology” working group at MARUM.

In a recent study, scientists from the department Living Matter Physics at MPI-DS developed a model describing communication pathways in bacterial populations. Bacteria show an overall organizational pattern by sensing the concentration of chemicals in their environment and adapting their motion.

The structure only becomes visible on a higher level

“We modeled the non-reciprocal interaction between two bacterial species,” first author Yu Duan explains. “This means that species A is chasing species B, whereas B is aiming to repel from A,” he continues. The researchers found, that just this chase-and-avoid interaction is sufficient to form a structural pattern. The type of the resulting pattern depends on the strength of the interaction. This complements a previous study, where a model was proposed that also included intraspecies interactions of the bacteria in order to form a pattern.

In this new model, which also includes the effect of bacterial motility, neither adhesion nor alignment are required to form complex super-structures encompassing millions of individuals. “Although the bacterial population dynamics show a global order, this is not the case on the individual bacterial level. In particular, a single bacterium seems to move in a disordered way, with the structure becoming visible only on a higher level, which is very fascinating,” summarizes Benoît Mahault, group leader in the department Living Matter Physics at MPI-DS.

A general model for collective behavior

The model also allows to consider more than two species, increasing the amount of possible interactions and emerging patterns. Notably, it is also not limited to bacteria but can be applied to a variety of collective behaviors. These include light-controlled microswimmers, social insects, animal groups and robotic swarms. The study therefore provides general insights on the mechanisms responsible for the formation of large-scale structures in networks with many components.

The new study reports the preservation of molecular fragments of the pigment phaeomelanin in 10-million-year-old frogs, adding molecular analysis to the palaeontologists’ arsenal when reconstructing the original colours of extinct organisms.

The study, published today in Nature Communications, was led by palaeontologists Dr Tiffany Slater and Prof. Maria McNamara of UCC’s School of Biological, Earth, and Environmental Sciences (BEES) and Environmental Research Institute (ERI). They worked with an international team of scientists at Fujita Health University (Japan), Linyi University (China) and Lund University (Sweden).

Dr Slater said:

“This finding is so exciting because it puts palaeontologists in a better place to detect different melanin pigments in many more fossils.

“This will paint a more accurate picture of ancient animal colour and will answer important questions about the evolution of colours in animals. Scientists still don’t know how — or why — phaeomelanin evolved because it is toxic to animals, but the fossil record might just unlock the mystery.”

The team performed rigorous laboratory experiments on black, ginger, and white feathers to track how phaeomelanin pigments degrade during the fossilisation process, which backs up their interpretations of the fossil chemistry.

Prof. McNamara, senior author on the study, said,

“Fossils are invariably altered by the ravages of heat and pressure during burial, but that doesn’t mean that we lose all original biomolecular information. Our fossilization experiments were the key to understanding the chemistry of the fossils, and prove that traces of biomolecules can survive being cooked during the fossilization process.

“There is huge potential to explore the biochemical evolution of animals using the fossil record, when we account for chemical changes during fossilization.”

Dark matter may be the most sought-for constituent of our universe. Surprisingly, this mysterious form of matter, that physicist and astronomers so far have not been able to detect, is assumed to make up an enormous part of what is out there. No less than 85% of matter in the universe is suspected to be ‘dark’, presently only noticeable through the gravitational pull it exerts on other astronomical objects. Understandably, scientists want more. They want to really see dark matter — or at the very least, detect its presence directly, not just infer it from gravitational effects. And, of course: they want to know what it is.

Cleaning up two problems

One thing is clear: dark matter cannot be the same type of matter that you and I are made of. If that were to be the case, dark matter would simply behave like ordinary matter — it would form objects like stars, light up, and no longer be ‘dark’. Scientists are therefore looking for something new — a type of particle that nobody has detected yet, and that probably only interacts very weakly with the types of particles that we know, explaining why this constituent of our world so far has remained elusive.

There are plenty of clues for where to look. One popular assumption is that dark matter could be made of axions. This hypothetical type of particle was first introduced in the 1970s to resolve a problem that had nothing to do with dark matter. The separation of positive and negative charges inside the neutron, one of the building blocks of ordinary atoms, turned out to be unexpectedly small. Scientists of course wanted to know why. It turned out that the presence of a hitherto undetected type of particle, interacting very weakly with the neutron’s constituents, could cause exactly such an effect. The later Nobel Prize winner Frank Wilczek came up with a name for the new particle: axion — not just similar to other particle names like proton, neutron, electron and photon, but also inspired by a laundry detergent of the same name. The axion was there to clean up a problem.

In fact, despite never being detected, it might clean up two. Several theories for elementary particles, including string theory, one of the leading candidate theories to unify all forces in nature, appeared to predict that axion-like particles could exist. If axions were indeed out there, could they also constitute part or even all of the missing dark matter? Perhaps, but an additional question that haunted all dark matter research was just as valid for axions: if so, then how can we see them? How does one make something ‘dark’ visible?

Shining a light on dark matter

Fortunately, it seems that for axions there may be a way out of this conundrum. If the theories that predict axions are correct, they are not only expected to be mass-produced in the universe, but some axions could also be converted into light in the presence of strong electromagnetic fields. Once there is light, we can see. Could this be the key to detect axions — and therefore to detect dark matter?

To answer that question, scientists first had to ask themselves where in the universe the strongest known electric and magnetic fields occur. The answer is: in regions surrounding rotating neutron stars also known as pulsars. These pulsars — short for ‘pulsating stars’ — are dense objects, with a mass roughly the same as that of our Sun, but a radius that is around 100,000 times smaller, only about 10 km. Being so small, pulsars spin with enormous frequencies, emitting bright narrow beams of radio emission along their axis of rotation. Similar to a lighthouse, the pulsar’s beams can sweep across the Earth, making the pulsating star easily observable.

However, the pulsar’s enormous spin does more. It turns the neutron star into an extremely strong electromagnet. That, in turn, could mean that pulsars are very efficient axion factories. Every single second an average pulsar would be capable of producing a 50-digit number of axions. Because of the strong electromagnetic field around the pulsar, a fraction of these axions could convert into observable light. That is: if axions exist at all — but the mechanism can now be used to answer just that question. Just look at pulsars, see if they emit extra light, and if they do, determine whether this extra light could be coming from axions.

Simulating a subtle glow

As always in science, actually performing such an observation is of course not that simple. The light emitted by axions — detectable in the form of radio waves — would only be a small fraction of the total light that these bright cosmic lighthouses send our way. One needs to know very precisely what a pulsar without axions would look like, and what a pulsar with axions would look like, to be able to see the difference — let alone to quantify that difference and turn it into a measurement of an amount of dark matter.

This is exactly what a team of physicists and astronomers have now done. In a collaborative effort between the Netherlands, Portugal and the USA, the team has constructed a comprehensive theoretical framework which allows for the detailed understanding of how axions are produced, how axions escape the gravitational pull of the neutron star, and how, during their escape, they convert into low energy radio radiation.

The theoretical results were then put on a computer to model the production of axions around pulsars, using state-of-the-art numerical plasma simulations that were originally developed to understand the physics behind how pulsars emit radio waves. Once virtually produced, the propagation of the axions through the electromagnetic fields of the neutron star was simulated. This allowed the researchers to quantitatively understand the subsequent production of radio waves and model how this process would provide an additional radio signal on top of the intrinsic emission generated from the pulsar itself.

Putting axion models to a test

The results from theory and simulation were then put to a first observational test. Using observations from 27 nearby pulsars, the researchers compared the observed radio waves to the models, to see if any measured excess could provide evidence for the existence of axions. Unfortunately, the answer was ‘no’ — or perhaps more optimistically: ‘not yet’. Axions do not immediately jump out to us, but perhaps that was not to be expected. If dark matter were to give up its secrets that easily, it would already have been observed a long time ago.

The hope for a smoking-gun detection of axions, therefore, is now on future observations. Meanwhile, the current non-observation of radio signals from axions is an interesting result in itself. The first comparison between simulations and actual pulsars has placed the strongest limits to date on the interaction that axions can have with light.

Of course, the ultimate goal is to do more than just set limits — it is to either show that axions are out there, or to make sure that it is extremely unlikely that axions are a constituent of dark matter at all. The new results are just a first step in that direction; they are only the beginning of what could become an entirely new and highly cross-disciplinary field that has the potential to dramatically advance the search for axions.

The breakthrough centers on a specific usage of neural networks that has become popular in recent years — tackling challenging biological questions. Among these are examinations of the intricacies of RNA splicing — the focal point of the study — which plays a role in transferring information from DNA to functional RNA and protein products.

“Many neural networks are black boxes — these algorithms cannot explain how they work, raising concerns about their trustworthiness and stifling progress into understanding the underlying biological processes of genome encoding,” says Oded Regev, a computer science professor at NYU’s Courant Institute of Mathematical Sciences and the senior author of the paper, which appears in the Proceedings of the National Academy of Sciences. “By harnessing a new approach that improves both the quantity and the quality of the data for machine-learning training, we designed an interpretable neural network that can accurately predict complex outcomes and explain how it arrives at its predictions.”

Regev and the paper’s other authors, Susan Liao, a faculty fellow at the Courant Institute, and Mukund Sudarshan, a Courant doctoral student at the time of the study, created a neural network based on what is already known about RNA splicing.

Specifically, they developed a model — the data-driven equivalent of a high-powered microscope — that allows scientists to trace and quantify the RNA splicing process, from input sequence to output splicing prediction.

“Using an ‘interpretable-by-design’ approach, we’ve developed a neural network model that provides insights into RNA splicing — a fundamental process in the transfer of genomic information,” notes Regev. “Our model revealed that a small, hairpin-like structure in RNA can decrease splicing.”

The researchers confirmed the insights their model provides through a series of experiments. These results showed a match with the model’s discovery: Whenever the RNA molecule folded into a hairpin configuration, splicing was halted, and the moment the researchers disrupted this hairpin structure, splicing was restored.

The research was supported by grants from the National Science Foundation (MCB-2226731), the Simons Foundation, the Life Sciences Research Foundation, an Additional Ventures Career Development Award, and a PhRMA Fellowship.