Why do people hurt the ones they claim to love? That question has driven researchers to discover much about the psychological and sociological predictors and consequences of intimate partner aggression. But an understanding of the neurobiological causes — or what happens in the brain — remains incomplete.
A new study led by Virginia Commonwealth University researchers used functional magnetic resonance imaging to examine the brain activity of 51 male-female romantic couples as they experienced intimate partner aggression in real time.
They found that aggression toward intimate partners was associated with aberrant activity in the brain’s medial prefrontal cortex, or MPFC, which has many functions, but among them is the ability to foster perceptions of closeness with and value of other people.
“We found that aggression towards intimate partners has a unique signature in the brain,” said lead author David Chester, Ph.D., an associate professor in the Department of Psychology in the College of Humanities and Sciences. “There is something distinct happening at the neural level when people decide whether to harm their romantic partners, a process that differs in a meaningful way from decisions about whether to harm friends or strangers.”
The research was led by Chester’s Social Psychology and Neuroscience Lab, which seeks to understand the psychological and biological processes that motivate and constrain aggressive behavior. The study, “Neural Mechanisms of Intimate Partner Aggression,” will be published in the journal Biological Psychology.
The researchers were able to observe couples’ brain activity during intimate partner aggression by asking participants to play a computer game against three people, one at a time: their romantic partner, a close friend and a stranger. In reality, they were playing against a computer.

The University of Surrey and the School of Dentistry at the University of Birmingham have developed a new technique to improve understanding of how acid damages teeth at the microstructural level.
The researchers performed a technique called “in situ synchrotron X-ray microtomography” at Diamond Light Source, a special particle accelerator facility with which the University of Surrey has a strong working partnership. There, electrons were accelerated to near light speed to generate bright X-rays that were used to scan dentine samples while they were being treated with acid. This enabled the team to build clear 3D images of dentine’s internal structure with sub-micrometre resolution (a micrometre being one-thousandth of a millimetre). By analysing these images over the six hours of the experiment, the researchers conducted the first-ever time-resolved 3D study (often referred to as 4D studies) of the dentine microstructural changes caused by acid.
The study, published in Dental Materials, highlights that acid dissolves the minerals in different structures of dentine at different rates. Dentine forms the main bulk of human teeth and supports the enamel, which covers the crown surface, helping to make teeth strong and resilient, but acids from dental plaque can cause tooth decay which affects the integrity of the dental structure. This research aims to develop knowledge that leads to new treatments that can restore the structure and function of dentine.
Dr Tan Sui, Senior Lecturer in Materials Engineering at the University of Surrey, who led the research group, said:
“Relatively little is known about how exactly acid damages the dentine inside our teeth at a microstructural level. This new research technique changes that and opens the possibility of helping identify new ways to protect dental tissues and develop new treatments.”
Nathanael Leung, a final year PhD student at the University of Surrey, has been awarded a GSK Award 2021 by the Oral and Dental Research Trust. He will continue to study the mechanical response of dentine to masticatory forces in correlation with the microstructural changes that acid causes as well as in response to different treatments like fillings and crowns.
This research is part of an ongoing collaboration with Prof Gabriel Landini and Dr Richard Shelton at the School of Dentistry, University of Birmingham.
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A new computational analysis suggests that, beyond the initial effect of one infected person arriving and spreading disease to a previously uninfected population, the continuous arrival of more infected individuals has a significant influence on the evolution and severity of the local outbreak. Mattia Mazzoli, Jose Javier Ramasco, and colleagues present these findings in the open-access journal PLOS Computational Biology.
In light of the ongoing COVID-19 pandemic, much research has investigated the dynamics of local outbreaks caused by the first detected cases in a population, which are linked to travel. However, few studies have explored whether and how the arrival of multiple infected individuals might impact the development of a local outbreak — a situation termed “multi-seeding.”
To examine the impact of multi-seeding, Mazzoli and colleagues first simulated local outbreaks in Europe using a computational modeling approach. To capture travel and seeding events, the simulations incorporated real-world location data from mobile phones during March 2020, when the COVID-19 pandemic began.
These simulations suggested that there is indeed an association between the number of “seed” arrivals per local population and the speed of spread, the final number of people infected, and the peak incidence rate experienced by the population. This relationship appears to be complex and non-linear, and it depends on the details of the social contact network within the affected population, including the effects of lockdowns.
To test whether the simulations accurately reflect real-world outbreaks, the researchers looked for similar associations between mobility data and COVID-19 incidence and mortality during the first wave of COVID-19 infection in England, France, Germany, Italy, and Spain. This analysis revealed strong signs of real-world multi-seeding effects similar to those observed in the simulations.
Based on these findings, the researchers propose a method to understand and reconstruct the spatial spreading patterns of the main outbreak-producing events in every country.
“Now that the relevance of multi-seeding is understood, it is crucial to develop containment measures that take it into account,” Ramasco says. Next, the researchers hope to incorporate the effects of vaccinations and antibodies acquired through infection into their simulations.
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Researchers from The University of Tokyo Institute of Industrial Science have found that infection with the measles virus activates not one but two different branches of the innate immune system. This is because of the effect of the measles virus on small structures within cells called mitochondria.
Measles is a significant disease worldwide, causing high levels of child mortality. Viral genomes can be made of either RNA or DNA, and the host immune response to each differs. RNA viruses such as the measles virus activate a molecule called RIG-I, whereas DNA viruses activate a different molecule called cGAS. These molecules then trigger a cascade of activation of other molecules such as interferon, leading to an immune response to the virus.
The team have now shown that infection with measles virus leads to the activation of both the RNA and DNA virus immune responses. Measles virus affects the mitochondria within the cell, interfering with their growth and division and causing them to fuse together. Mitochondria are essential for cellular energy production and contain a small circular DNA molecule, and the actions of the measles virus cause this mitochondrial DNA to be released into the cell. This release of DNA into the cytoplasm of the cell, where usually no DNA is found, triggers the cGAS immune response just as a DNA virus would. This response occurs after the immune response to RNA viruses caused by the measles virus itself.
“We first showed mitochondrial abnormalities in measles-infected cultured cells using imaging techniques,” says lead author Hiroki Sato. “Then we confirmed the presence of mitochondrial DNA in the cytosol of infected cells through biochemical analysis, and then carried out experiments on mice lacking the cGAS protein to show that the immune response was also caused by the cGAS pathway.”
This is the first time that single and negative strand RNA viruses have been shown to activate the cGAS pathway. “We suggest that there are two steps to measles infection,” says senior author Chieko Kai. “In the first, early phase, viral RNA replication is detected by the RNA-sensing immune response, and then in a second, later phase, mitochondrial downregulation and release of mitochondrial DNA cause prolonged interferon production.”
The team then found evidence in previously published datasets to suggest that this response can also be triggered by other viruses that affect the growth and development of mitochondria. They therefore suggest that this is an important host mechanism for a full immune response to such viruses. Increased understanding of how the body works to combat an infection such as measles may help to eradicate this disease for good.
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Cambridge researchers have discovered how T cells — an important component of our immune system — are able keep on killing as they hunt down and kill cancer cells, repeatedly reloading their toxic weapons.
Cytotoxic T cells are specialist white blood cells that are trained by our immune system to recognise and eliminate threats — including tumour cells and cells infected with invading viruses, such as SARS-CoV-2, which causes COVID-19. They are also at the heart of new immunotherapies that promise to transform cancer treatment.
Professor Gillian Griffiths from the Cambridge Institute for Medical Research, who led the research, said: “T cells are trained assassins that are sent on their deadly missions by the immune system. There are billions of them in our blood, each engaged in a ferocious and unrelenting battle to keep us healthy.
“Once a T cell has found its target, it binds to it and releases its toxic cargo. But what is particularly remarkable is that they are then able to go on to kill and kill again. Only now, thanks to state-of-the-art technologies, have we been able to find out how they reload their weapons.”
Today, in a study published in Science, the team have shown that the refuelling of T cells’ toxic weapons is regulated by mitochondria. Mitochondria are often referred to as a cell’s batteries as they provide the energy that power their function. However, in this case the mitochondria use an entirely different mechanism to ensure the killer T cells have sufficient ‘ammunition’ to destroy their targets.
Professor Griffiths added: “These assassins need to replenish their toxic payload so that they can keep on killing without damaging the T cells themselves. This careful balancing act turns out to be regulated by the mitochondria in T cells, which set the pace of killing according to how quickly they themselves can manufacture proteins. This enables killer T cells to stay healthy and keep on killing under challenging conditions when a prolonged response is required.”
To accompany the study, Professor Griffiths and colleagues have released footage showing killer T cells as they hunt down and eliminate cancer cells.
One teaspoon full of blood alone is believed to have around 5 million T cells, each measuring around 10 micrometres in length, about a tenth the width of a human hair. The cells move around rapidly, investigating their environment as they travel.
When a T cell finds an infected cell or, in the case of the film, a cancer cell, membrane protrusions rapidly explore the surface of the cell, checking for tell-tale signs that this is an uninvited guest. The T cell binds to the cancer cell and injects poisonous ‘cytotoxin’ proteins down special pathways called microtubules to the interface between the T cell and the cancer cell, before puncturing the surface of the cancer cell and delivering its deadly cargo.
The research was funded by Wellcome.
Video: https://www.youtube.com/watch?v=naMi4lYXm8Q
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Statins are a recommended and common intervention for preventing cardiovascular events by reducing levels of lipoprotein cholesterol in the blood. During the pandemic, it has been debated whether statins influence the risk of death from COVID-19. Researchers at Karolinska Institutet in Sweden have now conducted the largest population study to date in the field. The study, which is published in PLOS Medicine, indicates that statin treatment slightly lowers COVID-19 mortality.
Statins are used to lower the cholesterol level — the lipid count — in the blood and are a common preventative treatment in patients at high risk of cardiovascular events.
During the pandemic, the question of whether statins can reduce COVID-19 mortality via their effects on coagulation and the immune system has engaged scientists and doctors.
Earlier studies have not provided an unequivocal answer and have often suffered from the limitation that they have only included hospital inpatients. Researchers at Karolinska Institutet have now carried out the largest population study to date on the relationship between statins and COVID-19 mortality.
Using data from Swedish registers, the researchers followed 963,876 residents of Stockholm over the age of 45 between March and November 2020. The results are based on analyses of data on the participants’ prescribed medication and healthcare and from the Cause of Death Register.
The information was analysed with respect to such factors as diagnosed medical conditions. The results show that statin treatment was associated with a slightly lower risk of dying from COVID-19, a correlation that did not vary significantly among risk groups.
“Our results suggest that statin treatment can have a moderate prophylactic effect on COVID-19 mortality,” says co-first author Rita Bergqvist, medical student at Karolinska Institutet.
Randomised studies will be needed to ascertain whether there is a causal relationship, note the researchers.
“All in all, our findings support the continued use of statins for conditions such as cardiovascular disease and high levels of blood lipids in line with current recommendations during the COVID-19 pandemic,” says co-first author Viktor Ahlqvist, doctoral student at the Department of Global Public Health, Karolinska Institutet.
One limitation of the study concerns the use of prescription data without the possibility of checking individual drug use. The researchers were also not able to control for risk factors such as smoking and high BMI, only diagnosed health status.
The researchers received no financing for the study. Co-author Johan Sundström holds shares in Eli Lilly, Boehringer, Bayer, Pfizer, AstraZeneca and others; there are no other reported conflicts of interest.
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Clinical decisions made in the delivery setting as to whether to employ vaginal delivery or cesarean section are often made under high pressure, and with great uncertainty, and have serious consequences for mother and baby. Now, a new study of electronic health records spanning 86,000 deliveries suggests that if their prior patient had complications in one delivery mode, a physician will be more likely to switch to the other — and likely inappropriate — delivery mode for the subsequent patient, regardless of whether it is warranted for that patient’s indications.
Manasvini Singh, health economist at the University of Massachusetts Amherst and author of the study, which appears in the current issue of the journal Science, says this implies that physicians may sometimes rely not on scientific evidence, but on heuristics — simplified decision rules to aid complex decision-making — to determine their course of action, ultimately with sub-optimal effects on patient health.
Singh, an assistant professor of resource economics at UMass Amherst, analyzed inpatient electronic health record data across 21 years at the obstetric wards of two academic hospitals — one large and urban, the other small and suburban. Overall, the data covers 86,345 deliveries by 231 physicians, and she looked for complications such as obstructed labor, postpartum hemorrhage, fetal distress, perineal laceration, umbilical cord complications and obstetric trauma.
Singh found that depending on the model specification, complications in a prior cesarean delivery make the physician 0.6-2.4 percentage points more likely to switch to a vaginal delivery for the next patient, representing an increase of up to 3.4% in the probability of a vaginal delivery. Conversely, complications in a prior vaginal delivery make the physician 0.1-1.1 percentage points more likely to switch to a cesarean for the next patient, representing an increase of up to 3.6% in the probability of a cesarean delivery.
“Imagine that a patient’s vaginal delivery incurs a complication,” Singh explains. “The physician’s next patient now arrives for a vaginal delivery. Because of complications in the physician’s prior vaginal delivery, the physician will have a lower threshold — and therefore higher inclination — for deploying an emergency c-section during this next patient’s vaginal delivery, even if a cesarean is not clinically indicated for that patient. As a result, this next patient will be more likely to deliver via cesarean section.
“Now, imagine the converse example. The physician’s prior patient has a cesarean that
incurs complications. Assume the next patient comes in for a vaginal delivery. Now, because of complications in the physician’s prior cesarean delivery, the physician has a higher threshold — and therefore lower inclination — for deploying an emergency c-section during the vaginal delivery, even if a cesarean is clinically indicated for that patient. As a result, this next patient will be more likely to deliver vaginally.”
“There is no clinical reason why the delivery decisions for two separate patients — linked only by the accidental chance of being seen consecutively by the physician — should be causally related to each other,” Singh writes. “However, when faced with the complex decision of deciding whether the current patient is suited for a vaginal or a cesarean delivery, physicians may instead be influenced — sub-optimally — by the outcome of the decision they made for their prior patient.”
Singh says that there are three reasons why physicians’ use of such heuristics is especially concerning.
“First, the serious and long-term effects of inappropriate delivery mode choices on the health of mother and child are well documented, making the use of heuristics especially risky,” she says. “Several global campaigns have even been launched to make delivery decisions more evidence-based. Second, switching delivery modes after a complication does not offer any guaranteed benefits, making it a potentially flawed rule. There is no evidence that switching delivery modes after a complication avoids further complications. Finally, patients are usually more averse to having inappropriate procedures performed on them than they are to receiving unnecessary tests, which suggests that we should hold greater reservations about the use of heuristics in this setting.”
“Even without further evidence of patient harm, such deviations in delivery mode choices should be concerning given the long-term harm that inappropriate obstetric choices cause mother and baby,” Singh says.

Hundreds of connections between different human diseases have been uncovered through their shared origin in our genome by an international research team led by scientists from the Medical Research Council (MRC) Epidemiology Unit at the University of Cambridge, challenging the categorisation of diseases by organ, symptoms, or clinical specialty.
A new study published in Science today generated data on thousands of proteins circulating in our blood and combined this with genetic data to produce a map showing how genetic differences that affect these proteins link together seemingly diverse as well as related diseases.
Proteins are essential functional units of the human body that are composed of amino acids and coded for by our genes. Malfunctions of proteins cause diseases across most medical specialties and organ systems, and proteins are also the most common target of drugs that exist today.
The findings published today help explain why seemingly unrelated symptoms can occur at the same time in patients and suggest that we should reconsider how diverse diseases can be caused by the same underlying protein or mechanism. Where a protein is a drug target, this information can point to new strategies for treating a variety of conditions, as well as minimising adverse effects.
In the study using blood samples from over 10,000 participants from the Fenland study, the team led by senior author Dr Claudia Langenberg at the MRC Epidemiology Unit and Berlin Institute of Health at Charité Universitätsmedizin, Germany, demonstrated that natural variation in 2,500 regions of the human genome is very robustly associated with differences in abundance or function of 5,000 proteins circulating in the blood.
This approach addresses an important bottleneck in the translation of basic science to clinically actionable insights. While large scale studies of the human genome have identified many thousands of variants in our DNA sequence that are associated with disease, underlying mechanisms remain often poorly understood due to uncertainties in mapping those variants to genes. By linking such disease-related DNA variations to the abundance or function of an encoded protein, the team produced strong evidence for which genes are involved, and identified novel mechanisms by which proteins mediate genetic risk into disease onset.

Uses of facial images and facial recognition technologies — to unlock a phone or in airport security — are becoming increasingly common in everyday life. But how do people feel about using such data in healthcare and biomedical research?
Through surveying over 4,000 US adults, researchers found that a significant proportion of respondents considered the use of facial image data in healthcare across eight varying scenarios as unacceptable (15-25 percent). Taken with those that responded as unsure of whether the uses were acceptable, roughly 30-50 percent of respondents indicated some degree of concern for uses of facial recognition technologies in healthcare scenarios. Whereas using facial image data in some cases — such as to avoid medical errors, for diagnosis and screening, or for security — was acceptable to the majority, more than half of respondents did not accept or were uncertain about healthcare providers using this data to monitor patients’ emotions or symptoms, or for health research.
In the biomedical research setting, most respondents were equally worried about the use of medical records, DNA data and facial image data in a study.
While respondents were a diverse group in terms of age, geographic region, gender, racial and ethnic background, educational attainment, household income, and political views, their perspectives on these issues did not differ by demographics. Findings were published in the journal PLOS ONE.
“Our results show that a large segment of the public perceives a potential privacy threat when it comes to using facial image data in healthcare,” said lead author Sara Katsanis, who heads the Genetics and Justice Laboratory at Ann & Robert H. Lurie Children’s Hospital of Chicago and is a Research Assistant Professor of Pediatrics at Northwestern University Feinberg School of Medicine. “To ensure public trust, we need to consider greater protections for personal information in healthcare settings, whether it relates to medical records, DNA data, or facial images. As facial recognition technologies become more common, we need to be prepared to explain how patient and participant data will be kept confidential and secure.”
Senior author Jennifer K. Wagner, Assistant Professor of Law, Policy and Engineering in Penn State’s School of Engineering Design, Technology, and Professional Programs adds: “Our study offers an important opportunity for those pursuing possible use of facial analytics in healthcare settings and biomedical research to think about human-centeredness in a more meaningful way. The research that we are doing hopefully will help decisionmakers find ways to facilitate biomedical innovation in a thoughtful, responsible way that does not undermine public trust.”
The research team, which includes co-authors with expertise in bioethics, law, genomics, facial analytics, and bioinformatics, hopes to conduct further research to understand the nuances where public trust is lacking.
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It remains a central challenge in psychiatry to reliably judge whether a patient will respond to treatment. In a new study published in the journal Biological Psychiatry, researchers from Karolinska Institutet in Sweden and the Max Planck Institute for Human Development in Germany show that moment-to-moment fluctuations in brain activity can reliably predict whether patients with social anxiety disorder will be receptive to cognitive behavioural therapy (CBT).
Viable predictors of psychiatric treatment response are often sought, but remain elusive. Brain imaging techniques such as functional magnetic resonance imaging (fMRI) have shown promise, but low reliability has limited the utility of typical fMRI measures as harbingers of treatment success. Although historically considered a marker of ‘noise’ in the brain, moment-to-moment brain signal variability continues to gain momentum as a sensitive and reliable indicator of individual differences in the effectiveness of neural function. However, neural variability had not yet been examined in relation to psychiatric treatment outcomes.
To do so, the research team designed a unique study; 45 patients with social anxiety disorder had their brains imaged during passive rest and emotional face viewing (a social anxiety-relevant task) in two sessions (11 weeks apart) to capture moment-to-moment neural variability. Then, patients underwent a 9-week cognitive behavioural therapy delivered via the internet. The researchers showed that brain signal variability measured during the emotional task was the strongest and most reliable predictor of treatment outcome, despite the task only taking three minutes for patients to complete.
“Variability in brain signals is often considered measurement ‘noise,’ something to be eliminated prior to further analysis. We show first evidence that neural variability may be a reliable and efficient predictor of psychiatric treatment outcome, particularly when disorder-relevant task designs are utilized. We simply need to rethink our standard approaches in psychiatric neuroimaging to maximize clinical impact,” says lead author Dr. Kristoffer Månsson, clinical psychologist and researcher at the Department of Clinical Neuroscience, Karolinska Institutet.
In the next phase of their research, the authors will collect larger samples to examine whether brain signal variability can predict which specific treatment a patient should undergo.
“If moment-to-moment neural variability is to be worth its salt as a clinically useful predictor of treatment outcome, it needs to tell clinicians not only how much a patient will respond to a given treatment, but whether treatment A or B is better suited for them. Establishing this will be our long-term goal. In the meantime, our methods are immediately and openly available to any researcher interested in whether neural variability provides clinical utility within and beyond social anxiety disorder patients,” says senior author Dr. Douglas Garrett, leader of the Lifespan Neural Dynamics Group at the Max Planck UCL Centre for Computational Psychiatry and Ageing Research in Berlin.
The study was conducted in close collaboration with the Max Planck UCL Centre for Computational Psychiatry and Ageing Research and the Max Planck Institute for Human Development in Berlin, Germany, and Stockholm University, Uppsala University and the Umeå Functional Brain Imaging Centre in Sweden. It was financed by the Swedish Research Council, the Swedish Brain Foundation and the German Research Foundation. No conflicts of interest have been reported.
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