The atmosphere contains many tiny solid particles. Scientists from the Max Planck Institute for Dynamics and Self-Organization (MPI-DS) and the University of Göttingen in collaboration with the Centre national de la recherche scientifique (CNRS) in France and the university of Gothenburg, Sweden, now studied how such non-spherical particles settle in air. For this, they used a new precision apparatus equipped with high-speed cameras and a novel particle injection mechanism. Using a 3D-printer, they created particles of different shapes resembling discs of thickness as low as 50 micrometer and rods of length as high as 880 micrometers. Thanks to this setup, they could observe that particles tend to oscillate as they settle in quiescent air.

“So far, most studies on the behavior of such small particles were done with models in liquids since experiments in air are extremely challenging,” Mohsen Bagheri, group leader at MPI-DS, describes previous approaches. “However, the true settling dynamics could not be explored this way. They were now revealed in our experimental setting, directly measuring the motion of real-size particles, which are much heavier than the surrounding environment,” he continues.

The observed oscillation could impact the collision of individual particles, their travelling distance in the atmosphere and their interaction with the solar radiation.

Predicting the dynamics of particles

Typically, atmospheric particles are not perfectly spherical, but rather flattened or elongated structures. The scientists developed and tested a model to describe and predict the movement of such particles, which very accurately captures the experimental results. The new model can be used to study the dynamics and formation of particles clusters and the resulting effects in everyday life. “In particular, our results can help to better predict how long pollutants reside in the atmosphere or how precipitation is initiated in clouds,” summarizes Alain Pumir. The CNRS researcher developed the model together with his colleagues Bernhard Mehlig and Kristian Gustavsson.

In total, these new insights contribute to a more accurate understanding of atmospheric particles, and how they affect our environment and climate.

For the first time, researchers have identified the long-term health burden of bacterial meningitis. The bacterial infection can currently be cured with antibiotics, but it often leads to permanent neurological impairment. And since children are often affected, the consequences are significant.

“When children are affected, the whole family is affected. If a three-year-old child has impaired cognition, a motor disability, impaired or lost vision or hearing, it has a major impact. These are lifelong disabilities that become a major burden for both the individual and society, as those affected need health care support for the rest of their lives,” says Federico Iovino, associate professor in Medical Microbiology at the Department of Neuroscience, Karolinska Institutet, and one of the authors of the current study.

By analyzing data from the Swedish quality register on bacterial meningitis between 1987 and 2021, the researchers have been able to compare just over 3,500 people who contracted bacterial meningitis as children with just over 32,000 matched controls from the general population. The average follow-up time is over 23 years.

The results show that those diagnosed with bacterial meningitis consistently have a higher prevalence of neurological disabilities such as cognitive impairment, seizures, visual or hearing impairment, motor impairment, behavioral disorders, or structural damage to the head.

The risk was highest for structural head injuries — 26 times the risk, hearing impairment — almost eight times the risk, and motor impairment — almost five times the risk.

About one in three people affected by bacterial meningitis had at least one neurological impairment compared to one in ten among controls.

“This shows that even if the bacterial infection is cured, many people suffer from neurological impairment afterwards,” says Federico Iovino.

With the long-term effects of bacterial meningitis identified, Federico Iovino and his colleagues will now move forward with their research.

“We are trying to develop treatments that can protect neurons in the brain during the window of a few days it takes for antibiotics to take full effect. We now have very promising data from human neurons and are just entering a preclinical phase with animal models. Eventually, we hope to present this in the clinic within the next few years,” says Federico Iovino.

The research was funded by Merck & Co (in Sweden MSD).

Facts:

Bacterial meningitis is a rare but very serious infection that can affect people of all ages, but is most common in newborns, children and adolescents, and the elderly. It is often caused by pneumococcus (Streptococcus pneumoniae) which is also a major cause of bacterial respiratory infections such as pneumonia, otitis and sinusitis, which also mainly affect the youngest and oldest members of society.

Untreated, bacterial meningitis is fatal, but the infection can now be cured with antibiotics. However, antibiotics have difficulty penetrating the blood-brain barrier, which means that it takes time to fight the infection. During this time, nerve cells can be damaged and result in various permanent neurological damage. Furthermore, there is the constant threat of antibiotic-resistance to face in the clinics.

Source: Federico Iovino, Public Health Agency and Centers for Disease Control and Prevention.

The research team used six different questionnaires to determine the extent to which the participants had a materialistic attitude and tended to compare themselves with others, whether they used social media more actively or passively, whether they were addicted to social media, how stressed and how satisfied they were with their lives.

Downward spiral set in motion

“The data showed that a stronger materialistic approach goes hand in hand with a tendency to compare oneself with others,” points out Phillip Ozimek. This comparison is very easy to make on social media, primarily through passive use, i.e. by looking at the content posted by other users. Materialism and passive use were also linked to addictive use of social media. “By this we mean, for example, that users are constantly thinking about the respective channels and fear that they are missing out on something if they are not online,” explains Phillip Ozimek. This in turn leads to symptoms of poorer mental health, i.e. stress. The final link in the chain is reduced life satisfaction. “Social media is one of six stepping stones to unhappiness,” concludes Phillip Ozimek.

Social media attracts and breeds materialists

“Overall, the study provides further evidence that the use of social media is associated with risks, especially for people with a highly materialistic mindset,” says the psychologist. This is particularly worrying, because social media can trigger and increase materialistic values, for example through (influencer) marketing. At the same time, the platforms attract materialists anyway, as they are a perfect way to satisfy many materialistic needs.

“It’s definitely a good idea to be aware of the amount of time you spend on social media and to reduce it,” recommends Phillip Ozimek. He advises against giving up Social Media completely. “If you did, you’re likely to overcompensate.” The research team also suggests recording materialism and social media use in patients undergoing treatment for mental health disorders. “While these factors are often irrelevant, they can be a starting point for additional interventions that patients can try out at home.”

The study, published in Nature Human Behaviour and funded by Wellcome, uses an AI computational model — known as a generative neural network — to simulate how neural networks in the brain learn from and remember a series of events (each one represented by a simple scene).

The model featured networks representing the hippocampus and neocortex, to investigate how they interact. Both parts of the brain are known to work together during memory, imagination and planning.

Lead author, PhD student Eleanor Spens (UCL Institute of Cognitive Neuroscience), said: “Recent advances in the generative networks used in AI show how information can be extracted from experience so that we can both recollect a specific experience and also flexibly imagine what new experiences might be like.

“We think of remembering as imagining the past based on concepts, combining some stored details with our expectations about what might have happened.”

Humans need to make predictions to survive (e.g. to avoid danger or to find food), and the AI networks suggest how, when we replay memories while resting, it helps our brains pick up on patterns from past experiences that can be used to make these predictions.

Researchers played 10,000 images of simple scenes to the model. The hippocampal network rapidly encoded each scene as it was experienced. It then replayed the scenes over and over again to train the generative neural network in the neocortex.

The neocortical network learned to pass the activity of the thousands of input neurons (neurons that receive visual information) representing each scene through smaller intermediate layers of neurons (the smallest containing only 20 neurons), to recreate the scenes as patterns of activity in its thousands of output neurons (neurons that predict the visual information).

This caused the neocortical network to learn highly efficient “conceptual” representations of the scenes that capture their meaning (e.g. the arrangements of walls and objects) — allowing both the recreation of old scenes and the generation of completely new ones.

Consequently, the hippocampus was able to encode the meaning of new scenes presented to it, rather than having to encode every single detail, enabling it to focus resources on encoding unique features that the neocortex couldn’t reproduce — such as new types of objects.

The model explains how the neocortex slowly acquires conceptual knowledge and how, together with the hippocampus, this allows us to “re-experience” events by reconstructing them in our minds.

The model also explains how new events can be generated during imagination and planning for the future, and why existing memories often contain “gist-like” distortions — in which unique features are generalised and remembered as more like the features in previous events.

Senior author, Professor Neil Burgess (UCL Institute of Cognitive Neuroscience and UCL Queen Square Institute of Neurology), explained: “The way that memories are re-constructed, rather than being veridical records of the past, shows us how the meaning or gist of an experience is recombined with unique details, and how this can result in biases in how we remember things.”