This is according to researchers at the University of Cambridge’s Leverhulme Centre for the Future of Intelligence (CFI) in two articles published in the British Medical Journal, cautioning against blinkered use of AI for data-gathering and medical decision-making as we fight to regain normalcy in 2021.

“Relaxing ethical requirements in a crisis could have unintended harmful consequences that last well beyond the life of the pandemic,” said Dr Stephen Cave, Director of CFI and lead author of one of the articles.

“The sudden introduction of complex and opaque AI, automating judgments once made by humans and sucking in personal information, could undermine the health of disadvantaged groups as well as long-term public trust in technology.”

In a further paper, co-authored by CFI’s Dr Alexa Hagerty, researchers highlight potential consequences arising from the AI now making clinical choices at scale – predicting deterioration rates of patients who might need ventilation, for example – if it does so based on biased data.

Datasets used to “train” and refine machine-learning algorithms are inevitably skewed against groups that access health services less frequently, such as minority ethnic communities and those of “lower socioeconomic status”.

“COVID-19 has already had a disproportionate impact on vulnerable communities. We know these systems can discriminate, and any algorithmic bias in treating the disease could land a further brutal punch,” Hagerty said.

In December, protests ensued when Stanford Medical Centre’s algorithm prioritized home-workers for vaccination over those on the Covid wards. “Algorithms are now used at a local, national and global scale to define vaccine allocation. In many cases, AI plays a central role in determining who is best placed to survive the pandemic,” said Hagerty.

“In a health crisis of this magnitude, the stakes for fairness and equity are extremely high.”

Along with colleagues, Hagerty highlights the well-established “discrimination creep” found in AI that uses “natural language processing” technology to pick up symptom profiles from medical records – reflecting and exacerbating biases against minorities already in the case notes.

They point out that some hospitals already use these technologies to extract diagnostic information from a range of records, and some are now using this AI to identify symptoms of COVID-19 infection.

Similarly, the use of track-and-trace apps creates the potential for biased datasets. The researchers write that, in the UK, over 20% of those aged over 15 lack essential digital skills, and up to 10% of some population “sub-groups” don’t own smartphones.

“Whether originating from medical records or everyday technologies, biased datasets applied in a one-size-fits-all manner to tackle COVID-19 could prove harmful for those already disadvantaged,” said Hagerty.

In the BMJ articles, the researchers point to examples such as the fact that a lack of data on skin colour makes it almost impossible for AI models to produce accurate large-scale computation of blood-oxygen levels. Or how an algorithmic tool used by the US prison system to calibrate reoffending – and proven to be racially biased – has been repurposed to manage its COVID-19 infection risk.

The Leverhulme Centre for the Future of Intelligence recently launched the UK’s first Master’s course for ethics in AI. For Cave and colleagues, machine learning in the Covid era should be viewed through the prism of biomedical ethics – in particular the “four pillars”.

The first is beneficence. “Use of AI is intended to save lives, but that should not be used as a blanket justification to set otherwise unwelcome precedents, such as widespread use of facial recognition software,” said Cave.

In India, biometric identity programs can be linked to vaccination distribution, raising concerns for data privacy and security. Other vaccine allocation algorithms, including some used by the COVAX alliance, are driven by privately owned AI, says Hagerty. “Proprietary algorithms make it hard to look into the ‘black box’, and see how they determine vaccine priorities.”

The second is ‘non-maleficence’, or avoiding needless harm. A system programmed solely to preserve life will not consider rates of ‘long covid’, for example. Thirdly, human autonomy must be part of the calculation. Professionals need to trust technologies, and designers should consider how systems affect human behaviour – from personal precautions to treatment decisions.

Finally, data-driven AI must be underpinned by ideals of social justice. “We need to involve diverse communities, and consult a range of experts, from engineers to frontline medical teams. We must be open about the values and trade-offs inherent in these systems,” said Cave.

“AI has the potential to help us solve global problems, and the pandemic is unquestionably a major one. But relying on powerful AI in this time of crisis brings ethical challenges that must be considered to secure public trust.”

Writing in The BMJ, Professor Tamsin Ford at the University of Cambridge and colleagues say deterioration in mental health is clearest among families already struggling and call for urgent action “to ensure that this generation is not disproportionately disadvantaged by COVID-19.”

They point to evidence that the mental health of the UK’s children and young people was deteriorating before the pandemic, while health, educational, and social outcomes for children with mental health conditions were worse in the 21st century than the late 20th century. For example, between 2004 and 2017 anxiety, depression, and self-harm increased, particularly among teenage girls.

Given that self-harm is an important risk factor for suicide, it is not surprising that rates of suicide among the UK’s children and young people also increased in recent years, they write, though numbers remain low compared with other age groups – about 100 people aged under 18 died by suicide each year in England between 2014 and 2016.

Studies carried out during the pandemic suggest that although some families are coping well, others are facing financial adversity, struggling to home school, and risk experiencing vicious cycles of increasing stress and distress.

Probable mental health conditions increased from 11% in 2017 to 16% in July 2020 across all age, sex, and ethnic groups according to England’s Mental Health of Children and Young People Survey (MHCYP). In addition, a sample of 2,673 parents recruited through social media reported deteriorating mental health and increased behavioural problems among children aged 4 to 11 years between March and May 2020 (during lockdown) but reduced emotional symptoms among 11-16 year olds.

The more socioeconomically deprived respondents had consistently worse mental health in both surveys, note the authors – a stark warning given that economic recession is expected to increase the numbers of families under financial strain.

The authors acknowledge that deteriorating mental health is by no means uniform. For example, a sizeable proportion of 19,000 8-18 year olds from 237 English schools surveyed during early summer 2020 reported feeling happier, while a quarter of young people in the MHCYP survey reported that lockdown had made their life better.

And while the incidence of self-harm recorded in primary care was substantially lower than expected for 10-17 year olds in April 2020, it returned to pre-pandemic levels by September 2020, with similar patterns detected for all mental health referrals in England.

Data also show a doubling in the number of urgent referrals for eating disorders in England during 2020, despite a smaller increase in non-urgent referrals.

Professor Tamsin Ford from the Department of Psychiatry at the University of Cambridge said: “Even before the pandemic, we were seeing deteriorating mental health among children and young people, which was amplified by inadequate service provision to support their needs. The lockdown and other measures aimed at tackling the pandemic will only serve to exacerbate these problems – and even more so for some different age groups and socioeconomic circumstances.

“Young people’s lives have been turned upside down by the pandemic, as is the case for lots of people, but their education has also been disrupted and many young people now face an uncertain future. We’re calling on policymakers to recognise the importance of education to social and mental health outcomes alongside an appropriate focus on employment and economic prospects.”

Reference
Ford, T. et al. Mental health of children and young people during pandemic. BMJ; 11 Mar 2020; DOI: 10.1136/bmj.n614

Adapted from a press release by The BMJ

While the volume of soft drinks purchased did not change, the amount of sugar in those drinks was 30g lower per household per week, which the researchers say represents a ‘win-win’ for public health and industry.

Sugary drinks have been linked to a number of health issues, including dental caries, obesity, type 2 diabetes and heart disease. In April 2018, the UK introduced a Soft Drinks Industry Levy explicitly designed to incentivise manufacturers to reduce the sugar content of soft drinks. The levy was placed on manufacturers, importers and bottlers rather than on consumers. It included two levy tiers: 24p per litre for ‘high tier’ drinks containing more than or equal to 8g total sugar per 100ml; and 18p per litre for ‘low tier’ drinks containing more than or equal to 5g and less than 8g total sugar per 100ml.

A team led by researchers from Cambridge’s Centre for Diet and Activity Research (CEDAR) at the MRC Epidemiology Unit analysed data from the Kantar Worldpanel, in which participating households are asked to record all food and drink purchases brought into the home. This included approximately 31 million purchases of drinks, confectionery and toiletries from March 2014 to March 2019.

The team divided soft drinks into three categories based on sugar content: high tier drinks, low tier drinks and no levy drinks (those with less than 5g total sugar per 100ml). As the Soft Drinks Industry Levy may have led households to substitute other drinks, they also examined purchasing of drinks exempt from the levy, including milk-based drinks, alcoholic drinks and no-added-sugar fruit juices.

The researchers compared purchases in March 2019 against a ‘counterfactual’ estimate – that is, an estimate based on pre-existing trends of how the purchases would look had the levy not taken place at all. This is the first analysis of the impact of the UK Soft Drinks Industry Levy on drink purchases that takes pre-existing trends into account. The results of the study, funded by the NIHR, are published today in The BMJ.

Prior to the introduction of the levy, the volume of high-tier drinks and amount of sugar associated was on a downward trend. However, even taking this trend into consideration, by March 2019, the volume of high tier drinks purchased had fallen by 155ml (44%) per household per week compared to the counterfactual estimate. The amount of sugar purchased in these drinks reduced by 18.0g per household per week, a 46% decrease.

For low tier drinks, the volume of drinks purchased was 177ml (86%) lower per household per week in March 2019 compared with the counterfactual estimate. The amount of sugar fell by 12.5g (an 86% decrease).

Although the volume of no levy drinks purchased didn’t change, as these soft drinks are not sugar-free and some increased in their sugar content, this meant that the sugar purchased from these drinks increased by 15.3g, equivalent to a 166% increase.

Overall, compared to the counterfactual estimate, there was no change in the volume of all soft drinks purchased in March 2019. However, there was a reduction in sugar purchased in all soft drinks (including exempt drinks) combined of 29.5g per household per week, equivalent to a 10% decrease.

The introduction of the Soft Drinks Industry Levy also coincided with significant decreases in purchasing of bottled water. However, the team say this reduction may be due to increases in concern about single-use plastic, which have been attributed, in the UK, to the broadcast of the BBC’s nature documentary series Blue Planet 2.

Dr David Pell from CEDAR, the study’s first author, said: “A 10% drop in the amount of sugar purchased from soft drinks might sound modest, but we know there’s an association between the amount of sugar drinks we consume and the risk of developing conditions such as obesity, type 2 diabetes and high blood pressure. Cutting out even a relatively small amount of sugar should have important impacts on the number of people with obesity and diabetes.”

Professor Martin White, also from the CEDAR, and the project lead, added: “The Soft Drinks Industry Levy appears to have led to a reduction in the amount of sugar that people are purchasing in soft drinks without impacting on the overall volume of soft drinks sold. It’s likely that this is due to manufacturers reformulating their products and reducing the sugar concentration in their drinks, as well as to consumers switching to lower sugar alternatives.

“This represents a valuable win-win for public health and the food industry – potentially improving people’s health with no detrimental effect on the volume of soft drinks that companies are selling.”

The research was funded by the National Institute for Health Research and the Medical Research Council. The Centre for Diet and Activity Research is funded by the British Heart Foundation, Cancer Research UK, the Economic and Social Research Council, the Medical Research Council, the National Institute for Health Research, and Wellcome.

Reference
Pell, D et al. Changes in British household purchases of soft drinks associated with implementation of the Soft Drinks Industry Levy: a controlled interrupted time series analysis. BMJ; 11 Mar 2021; DOI: 10.1136/bmj.n254

Researchers have found that out of the more than 300 COVID-19 machine learning models described in scientific papers in 2020, none of them is suitable for detecting or diagnosing COVID-19 from standard medical imaging, due to biases, methodological flaws, lack of reproducibility, and ‘Frankenstein datasets.’

The team of researchers, led by the University of Cambridge, carried out a systematic review of scientific manuscripts – published between 1 January and 3 October 2020 – describing machine learning models that claimed to be able to diagnose or prognosticate for COVID-19 from chest radiographs (CXR) and computed tomography (CT) images. Some of these papers had undergone the process of peer-review, while the majority had not.

Their search identified 2,212 studies, of which 415 were included after initial screening and, after quality screening, 62 studies were included in the systematic review. None of the 62 models was of potential clinical use, which is a major weakness, given the urgency with which validated COVID-19 models are needed. The results are reported in the journal Nature Machine Intelligence.

Machine learning is a promising and potentially powerful technique for detection and prognosis of disease. Machine learning methods, including where imaging and other data streams are combined with large electronic health databases, could enable a personalised approach to medicine through improved diagnosis and prediction of individual responses to therapies.

“However, any machine learning algorithm is only as good as the data it’s trained on,” said first author Dr Michael Roberts from Cambridge’s Department of Applied Mathematics and Theoretical Physics. “Especially for a brand-new disease like COVID-19, it’s vital that the training data is as diverse as possible because, as we’ve seen throughout this pandemic, there are many different factors that affect what the disease looks like and how it behaves.”

“The international machine learning community went to enormous efforts to tackle the COVID-19 pandemic using machine learning,” said joint senior author Dr James Rudd, from Cambridge’s Department of Medicine. “These early studies show promise, but they suffer from a high prevalence of deficiencies in methodology and reporting, with none of the literature we reviewed reaching the threshold of robustness and reproducibility essential to support use in clinical practice.”

Many of the studies were hampered by issues with poor quality data, poor application of machine learning methodology, poor reproducibility, and biases in study design. For example, several training datasets used images from children for their ‘non-COVID-19’ data and images from adults for their COVID-19 data. “However, since children are far less likely to get COVID-19 than adults, all the machine learning model could usefully do was to tell the difference between children and adults, since including images from children made the model highly biased,” said Roberts.

Many of the machine learning models were trained on sample datasets that were too small to be effective. “In the early days of the pandemic, there was such a hunger for information, and some publications were no doubt rushed,” said Rudd. “But if you’re basing your model on data from a single hospital, it might not work on data from a hospital in the next town over: the data needs to be diverse and ideally international, or else you’re setting your machine learning model up to fail when it’s tested more widely.”

In many cases, the studies did not specify where their data had come from, or the models were trained and tested on the same data, or they were based on publicly available ‘Frankenstein datasets’ that had evolved and merged over time, making it impossible to reproduce the initial results.

Another widespread flaw in many of the studies was a lack of involvement from radiologists and clinicians. “Whether you’re using machine learning to predict the weather or how a disease might progress, it’s so important to make sure that different specialists are working together and speaking the same language, so the right problems can be focused on,” said Roberts.

Despite the flaws they found in the COVID-19 models, the researchers say that with some key modifications, machine learning can be a powerful tool in combatting the pandemic. For example, they caution against naive use of public datasets, which can lead to significant risks of bias. In addition, datasets should be diverse and of appropriate size to make the model useful for different demographic group and independent external datasets should be curated.

In addition to higher quality datasets, manuscripts with sufficient documentation to be reproducible and external validation are required to increase the likelihood of models being taken forward and integrated into future clinical trials to establish independent technical and clinical validation as well as cost-effectiveness.

Reference:
Michael Roberts et al. ‘Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans.’ Nature Machine Intelligence (2021). DOI: 10.1038/s42256-021-00307-0

Ten years ago, Professor Dame Amanda Fisher, Director of the MRC London Institute of Medical Sciences (then Clinical Sciences Centre), and Vivienne Parry OBE, science writer and broadcaster, concocted an idea to celebrate the contributions that women scientists have made to their field, sometimes overlooked in favour of their male counterparts. With an endorsement from Dr Helen Pankhurst CBE, women’s rights activist and great-granddaughter of Emmeline Pankhurst, they called the awards scheme Suffrage Science.

Their awards were hand-crafted items of jewellery created by art students from Central Saint Martins-UAL, who worked with scientists to design pieces inspired by research and by the Suffragette movement. But rather than produce a new set of pieces for the next awards, each holder chose who they would like to pass their award onto, thus generating an extensive ‘family tree’ of incredible scientists and communicators.

As the relay continued, new branches of the Suffrage Science scheme were developed – the Engineering and Physical Sciences strand was founded in 2013, and the ‘Maths and Computing’ strand followed in 2016. The Suffrage Science family is now 148 strong, with a further 12 joining on Monday 8 March 2021, the tenth anniversary of the scheme.

Each previous holder chose to whom they wanted to pass their ‘heirloom’ piece of jewellery.

Professor Serena Best from Cambridge’s Department of Materials Science and Metallurgy, who was honoured in 2020, chose to pass her award to her colleague Professor Ruth Cameron. She said: “Professor Ruth Cameron is a highly successful and respected scientist in the field of biomaterials whose organisational abilities and communication skills are outstanding. Most recently, she has become the first female appointee to lead the Department of Materials Science and Metallurgy, University of Cambridge in the Office of Head of Department. Ruth’s work ethic will provide inspiration to the next generation of young female scientists – demonstrating that the key to success is collegial support and collaboration.”

Professor Róisín Owens from Cambridge’s Department of Chemical Engineering and Biotechnology, and Professor Melinda Duer from the Yusuf Hamied Department of Chemistry, were also named winners in 2020. Owens has chosen to pass her award to Professor Natalie Stingelin from Georgia Institute of Technology, and Duer has chosen to pass her award to Dr Mary Anti Chama from the University of Ghana.

“Natalie is a tremendous advocate for diversity in science and engineering,” said Owens. “She was incredibly supportive of me when I started out, mentoring me and suggesting my name for conferences and editorial work. She has worked tirelessly to support women and is very active on social media. She has brought countless young researchers, especially women under her wing, helping them to develop their careers. She is also very proactive in getting the old guard to be inclusive and diverse – including calling out conference organisers for not including women in their speaker lists. In her role as editor at RSC she has been very involved in trying to improve diversity and equality in publishing also.”

“I have known Mary since she was a Cambridge-Africa Research Fellow in Cambridge,” said Duer. “She impressed me then with how she approached interdisciplinary science, and brought in whatever techniques she needed in her quest to find new pharmaceutical compounds in plants. She has continued to impress me as she has developed her science and brought in new collaborators. She has been a champion for women in science throughout her career and very supportive of students and younger colleagues alike. I hope she won’t mind my saying that she also ensured that all her siblings had access to higher education – and now continues that with ensuring that her graduate students have what they need to be successful. I always enjoy any discussion with Mary – she has shown me how one can be kind, compassionate and still be ambitious in one’s science.”

Suffrage Science pioneer Professor Fisher said: “We dreamed up the awards scheme to celebrate the contribution that women have made to science, which often gets overlooked. This is as important now as it was ten years ago. This year’s awardees join a community of over 148 women scientists. I’m thrilled that since 2011, the awards have travelled from the UK, across Europe to the USA, Hong Kong, Iran and to Ghana, illustrating the international nature of science and engineering, and the global effort to improve the representation of women in STEM.”

The researchers, led by scientists at the University of Cambridge, say that the impact of COVID-19 on diphtheria vaccination schedules, coupled with a rise in the number of infections, risk the disease once more becoming a major global threat.

Diphtheria is a highly contagious infection that can affect the nose and throat, and sometimes the skin. If left untreated it can prove fatal. In the UK and other high-income countries, babies are vaccinated against infection. However, in low- and middle-income countries, the disease can still cause sporadic infections or outbreaks in unvaccinated and partially-vaccinated communities.

The number of diphtheria cases reported globally has being increasing gradually. In 2018, there were 16,651 reported cases, more than double the yearly average for 1996–2017 (8,105 cases).

Diphtheria is primarily caused by the bacterium Corynebacterium diphtheriae and is mainly spread by coughs and sneezes, or through close contact with someone who is infected. In most cases, the bacteria cause acute infections, driven by the diphtheria toxin – the key target of the vaccine. However, non-toxigenic C. diphtheria can also cause disease, often in the form of systemic infections.

In a study published today in Nature Communications,  an international team of researchers from the UK and India used genomics to map infections, including a subset from India, where over half of the globally reported cases occurred in 2018.

By analysing the genomes of 61 bacteria isolated from patients and combining these with 441 publicly available genomes, the researchers were able to build a phylogenetic tree – a genetic ‘family tree’ – to see how the infections are related and understand how they spread. They also used this information to assess the presence of antimicrobial resistance (AMR) genes and assess toxin variation.

The researchers found clusters to genetically-similar bacteria isolated from multiple continents, most commonly Asia and Europe. This indicates that C. diphtheriae has been established in the human population for at least over a century, spreading across the globe as populations migrated.

The main disease-causing component of C. diphtheriae is the diphtheria toxin, which is encoded by the tox gene. It is this component that is targeted by vaccines. In total, the researchers found 18 different variants of the tox gene, of which several had the potential to change the structure of the toxin.

Professor Gordon Dougan from the Cambridge Institute of Therapeutic Immunology and Infectious Disease (CITIID) said: ““The diphtheria vaccine is designed to neutralise the toxin, so any genetic variants that change the toxin’s structure could have an impact on how effective the vaccine is. While our data doesn’t suggest the currently used vaccine will be ineffective, the fact that we are seeing an ever-increasing diversity of tox variants suggests that the vaccine, and treatments that target the toxin, need to be appraised on a regular basis.”

Diphtheria infections can usually be treated with a number of classes of antibiotic. While C. diphtheriae resistant to antibiotics have been reported, the extent of such resistance remains largely unknown.

When the team looked for genes that might confer some degree of resistance to antimicrobials, they found that the average number of AMR genes per genome was increasing each decade. Genomes of bacteria isolated from infections from the most recent decade (2010-19) showed the highest average number of AMR genes per genome, almost four times as many on average than in the next highest decade, the 1990s.

Robert Will, a PhD student at CITIID and the study’s first author, said: “The C. diphtheriae genome is complex and incredibly diverse. It’s acquiring resistance to antibiotics that are not even clinically used in the treatment of diphtheria. There must be other factors at play, such as asymptomatic infection and exposure to a plethora of antibiotics meant for treating other diseases.”

Erythromycin and penicillin are the traditionally recommended antibiotics of choice for treating confirmed cases of early-stage diphtheria, though there are several different classes of antibiotics available to treat the infection. The team identified variants resistant to six of these classes in isolates from the 2010s, higher than in any other decades.

Dr Pankaj Bhatnagar from the World Health Organization country office for India said: “AMR has rarely been considered as a major problem in the treatment of diphtheria, but in some parts of the world, the bacterial genomes are acquiring resistance to numerous classes of antibiotics. There are likely to be a number of reasons to this, including exposure of the bacteria to antibiotics in their environment or in asymptomatic patients being treated against other infections.”

The researchers say that COVID-19 has had a negative impact on childhood vaccination schedules worldwide and comes at a time when reported case numbers are rising, with 2018 showing the highest incidence in 22 years.

Dr Ankur Mutreja from CITIID, who led the study, said: “It’s more important than ever that we understand how diphtheria is evolving and spreading. Genome sequencing gives us a powerful tool for observing this in real time, allowing public health agencies to take action before it’s too late.

“We mustn’t take our eye off the ball with diphtheria, otherwise we risk it becoming a major global threat again, potentially in a modified, better adapted, form.”

The research was funded primarily by the Medical Research Council, with additional support from the NIHR Cambridge Biomedical Research Centre.

Reference
Will, RC et al. Spatiotemporal persistence of multiple, diverse clades and toxins of Corynebacterium diphtheria. Nat Comms; 8 Mar 2021; DOI: 10.1038/s41467-021-21870-5 

Anyone who has drained a bathtub or stirred cream into coffee has seen a vortex, a ubiquitous formation that appears when fluid circulates. But unlike water, fluids governed by the strange rules of quantum mechanics have a special restriction: as was first predicted in 1945 by future Nobel winner Lars Onsager, a vortex in a quantum fluid can only twist by whole-number units.

These rotating structures are predicted to be widely useful for studying everything from quantum systems to black holes. But while the smallest possible quantum vortex, with a single unit of rotation, has been seen in many systems, larger vortices are not stable. While scientists have attempted to force larger vortices to hold themselves together, the results have been mixed: when the vortices have been formed, the severity of the methods used have generally destroyed their usefulness.

Now, Samuel Alperin and Professor Natalia Berloff from the University of Cambridge have discovered a theoretical mechanism through which giant quantum vortices are not only stable but form by themselves in otherwise near-uniform fluids. The findings, published in the journal Optica, could pave the way for experiments that might provide insight into the nature of rotating black holes that have similarities with giant quantum vortices.

To do this, the researchers used a quantum hybrid of light and matter, called a polariton. These particles are formed by shining laser light onto specially layered materials. “When the light gets trapped in the layers, the light and the matter become inseparable, and it becomes more practical to look at the resulting substance as something that is distinct from either light or matter, while inheriting properties of both,” said Alperin, a PhD student at Cambridge’s Department of Applied Mathematics and Theoretical Physics.

One of the most significant properties of polaritons comes from the simple fact that light can’t be trapped forever. A fluid of polaritons, which requires a high density of the exotic particles, is constantly expelling light, and needs to be fed with fresh light from the laser to survive. “The result,” said Alperin, “is a fluid which is never allowed to settle, and which doesn’t need to obey what are usually basic restrictions in physics, like the conservation of energy. Here the energy can change as a part of the dynamics of the fluid.”

It was exactly these constant flows of liquid light that the researchers exploited to allow the elusive giant vortex to form. Instead of shining the laser on the polariton fluid itself, the new proposal has the light shaped like a ring, causing a constant inward flow similarly to how water flows to a bathtub drain. According to the theory, this flow is enough to concentrate any rotation into a single giant vortex.

“That the giant vortex really can exist under conditions that are amenable to their study and technical use was quite surprising,” Alperin said, “but really it just goes to show how utterly distinct the hydrodynamics of polaritons are from more well-studied quantum fluids. It’s exciting territory.”

The researchers say that they are just at the beginning of their work on giant quantum vortices. They were able to simulate the collision of several quantum vortices as they dance around each other with ever increasing speed until they collide to form a single giant vortex analogous to the collision of black holes. They also explained the instabilities that limit the maximum vortex size while exploring intricate physics of the vortex behaviour.

“These structures have some interesting acoustic properties: they have acoustic resonances that depend on their rotation, so they sort of sing information about themselves,” said Alperin. “Mathematically, it’s quite analogous to the way that rotating black holes radiate information about their own properties.”

The researchers hope that the similarity could lead to new insights into the theory of quantum fluid dynamics, but they also say that polaritons might be a useful tool to study the behaviour of black holes.

Professor Berloff is jointly affiliated with Cambridge and the Skolkovo Institute of Science and Technology in Russia.

Reference:
Samuel N. Alperin and Natalia G. Berloff. ‘Multiply charged vortex states of polariton condensates.’ Optica (2021). DOI: 10.1364/OPTICA.418377

Care homes are at high risk of experiencing outbreaks of COVID-19, the disease caused by SARS-CoV-2. Older people and those affected by heart disease, respiratory disease and type 2 diabetes – all of which increase with age – are at greatest risk of severe disease and even death, making the care home population especially vulnerable.

Care homes are known to be high-risk settings for infectious diseases, owing to a combination of the underlying vulnerability of residents who are often frail and elderly, the shared living environment with multiple communal spaces, and the high number of contacts between residents, staff and visitors in an enclosed space.

In research published today in eLife, a team led by scientists at the University of Cambridge and Wellcome Sanger Institute used a combination of genome sequencing and detailed epidemiological information to examine the impact of COVID-19 on care homes and to look at how the virus spreads in these settings.

SARS-CoV-2 is an RNA virus and as such its genetic code is prone to errors each time it replicates. It is currently estimated that the virus mutates at a rate of 2.5 nucleotides (the A, C, G and U of its genetic code) per month. Reading – or ‘sequencing’ – the genetic code of the virus can provide valuable information on its biology and transmission. It allows researchers to create ‘family trees’ – known as phylogenetic trees – that show how samples relate to each other.

Scientists and clinicians in Cambridge have pioneered the use of genome sequencing and epidemiological information to trace outbreaks and transmission networks in hospitals and community-based healthcare settings, helping inform infection control measures and break the chains of transmission. Since March 2020, they have been applying this method to SARS-CoV-2 as part of the COVID-19 Genomics UK (COG-UK) Consortium.

In this new study, researchers analysed samples collected from 6,600 patients between 26 February and 10 May 2020 and tested at the Public Health England (PHE) Laboratory in Cambridge. Out of all the cases, 1,167 (18%) were care home residents from 337 care homes, 193 of which were residential homes and 144 nursing homes, the majority in the East of England. The median age of care home residents was 86 years.

While the median number of cases per care home was two, the ten care homes with the largest number of cases accounted for 164 cases. There was a slight trend for nursing homes to have more cases per home than residential homes, with a median of three cases.

Compared with non-care home residents admitted to hospital with COVID-19, hospitalised care home residents were less likely to be admitted to intensive care units (less than 7% versus 21%) and more likely to die (47% versus 20%).

The researchers also explored links between care homes and hospitals. 68% of care home residents were admitted to hospital during the study period. 57% were admitted with COVID-19, 6% of cases had suspected hospital-acquired infection, and 33% were discharged from hospital within 7 days of a positive test. These findings highlight the ample opportunities for SARS-CoV-2 transmission between hospital and care home settings.

When the researchers examined the viral sequences, they found that for several of the care homes with the highest number of cases, all of the cases clustered closely together on a phylogenetic tree with either identical genomes or just one base pair difference. This was consistent with a single outbreak spreading within the care home.

By contrast, for several other care homes, cases were distributed across the phylogenetic tree, with more widespread genetic differences, suggesting that each of these cases was independent and not related to a shared transmission source.

“Older people, particularly those in care homes who may be frail, are at particular risk from COVID-19, so it’s essential we do all that we can to protect them,” said Dr Estée Török, an Honorary Consultant at Addenbrooke’s Hospital, Cambridge University Hospitals (CUH), and an Honorary Senior Visiting Fellow at the University of Cambridge.

“Preventing the introduction of new infections into care homes should be a key priority to limit outbreaks, alongside infection control efforts to limit transmission within care homes, including once an outbreak has been identified.”

The team found two clusters that were linked to healthcare workers. One of these involved care home residents, a carer from that home and another from an unknown care home, paramedics and people living with them. The second involved several care home residents and acute medical staff at Cambridge University Hospitals NHS Foundation Trust who cared for at least one of the residents. It was not possible to say where these clusters originated from and how the virus spread.

“Using this technique of ‘genomic surveillance’ can help institutions such as care homes and hospitals better understand the transmission networks that allow the spread of COVID-19,” added Dr William Hamilton from the University of Cambridge and CUH. “This can then inform infection control measures, helping ensure that these places are as safe as possible for residents, patients, staff and visitors.”

The absolute number of diagnosed COVID-19 cases from care home residents declined more slowly in April than for non-care home residents, increasing the proportion of cases from care homes and contributing to the slow rate of decline in total case numbers during April and early May 2020.

“Our data suggest that care home transmission was more resistant to lockdown measures than non-care home settings. This may reflect the underlying vulnerability of the care home population, and the infection control challenges of nursing multiple residents who may also share communal living spaces,” said Gerry Tonkin-Hill from the Wellcome Sanger Institute.

The team found no new viral lineages from outside the UK, which may reflect the success of travel restrictions in limiting new viral introductions into the general population during the first epidemic wave and lockdown period.

This work was funded by COG-UK, Wellcome, the Academy of Medical Sciences, the Health Foundation and the NIHR Cambridge Biomedical Research Centre.

Reference
Hamilton, W et al. COVID-19 infection dynamics in care homes in the East of England: a retrospective genomic epidemiology study. eLife; 2 March 2021; DIO: 10.7554/eLife.64618

Polaritons are quantum particles that consist of a photon and an exciton, another quasiparticle, combining light and matter in a curious union that opens up a multitude of possibilities in next-generation devices.

The researchers have shown that geometrically coupled polariton condensates, which appear in semiconductor devices, are capable of simulating molecules with various properties.

Ordinary molecules are groups of atoms bound together with molecular bonds, and their physical properties differ from those of their constituent atoms quite drastically: consider the water molecule, H₂O, and elemental hydrogen and oxygen.

“In our work, we show that clusters of interacting polaritonic and photonic condensates can form a range of exotic and entirely distinct entities – ‘molecules’ – that can be manipulated artificially,” said first author Alexander Johnston, from Cambridge Department of Applied Mathematics and Theoretical Physics. “These artificial molecules possess new energy states, optical properties, and vibrational modes from those of the condensates comprising them.”

Johnston and his colleagues – Kirill Kalinin from DAMTP and Professor Natalia Berloff, who holds joint positions at Cambridge and Skoltech – were running numerical simulations of two, three, and four interacting polariton condensates, when they noticed some curious asymmetric stationary states in which not all of the condensates have the same density in their ground state.

“Upon further investigation, we found that such states came in a wide variety of different forms, which could be controlled by manipulating certain physical parameters of the system,” said Johnston. “This led us to propose such phenomena as artificial polariton molecules and to investigate their potential uses in quantum information systems.”

In particular, the team focused on an ‘asymmetric dyad’, which consists of two interacting condensates with unequal occupations. When two of those dyads are combined into a tetrad structure, the latter is, in some sense, analogous to a homonuclear molecule – for instance, to molecular hydrogen H₂. Furthermore, artificial polariton molecules can also form more elaborate structures, which could be thought of as artificial polariton compounds.

“There is nothing preventing more complex structures from being created,” said Johnston. “We’ve found that there is a wide range of exotic, asymmetric states possible in tetrad configurations. In some of these, all condensates have different densities, despite all of the couplings being of equal strength, inviting an analogy with chemical compounds.”

In specific tetrad structures, each asymmetric dyad can be viewed as an individual ‘spin,’ defined by the orientation of the density asymmetry. This has interesting consequences for the system’s degrees of freedom, or the independent physical parameters required to define states. The spins introduce a separate degree of freedom, in addition to the continuous degrees of freedom given by the condensate phases.

The relative orientation of each of the dyads can be controlled by varying the coupling strength between them. Since quantum information sem.

“In addition, we have discovered a plethora of exotic asymmetric states in triad and tetrad systems,” said Berloff. “It is possible to seamlessly transition between such states simply by varying the pumping strength used to form the condensates. This property suggests that such states could form the basis of a polaritonic multi-valued logic system, which could enable the development of polaritonic devices that dissipate significantly less power than traditional methods and, potentially, operate orders of magnitude faster.”

Reference:
Alexander Johnston, Kirill P. Kalinin, and Natalia G. Berloff. ‘Artificial polariton molecules.’ Physical Review Letters B (2021). DOI: 10.1103/PhysRevB.103.L060507

Adapted from a Skoltech press release.

The results, published today in the journal Proceedings of the Royal Society B, provide the first evidence of a link between self-control and intelligence in a non-primate species.

To conduct the experiment, common cuttlefish (Sepia officinalis) in tanks were presented with two foods they commonly eat, each in a separate Perspex chamber. In one chamber was a piece of king prawn, which they could eat immediately. In the other was a live grass shrimp, their preferred food, but they could only have the shrimp if they waited and didn’t eat the prawn.

A range of delays were tested, starting at 10 seconds and increasing by 10 seconds each time. All six cuttlefish in the experiment showed self-control, waiting for the grass shrimp and ignoring the king prawn. Those with the most self-control could wait 130 seconds for the grass shrimp to be released – an ability comparable with large-brained animals like chimpanzees.

“It was quite astonishing that the cuttlefish could wait for over two minutes for a better snack. Why would a fast-growing animal with an average life-span of less than two years be a picky eater?” said Dr Alexandra Schnell in the University of Cambridge’s Department of Psychology, first author of the paper.

The learning ability of each cuttlefish was then tested in a different task. A dark grey marker and a white marker were placed in random positions in the tank. After learning to associate one colour with a reward, the reward was switched to be associated with the other colour. The cuttlefish that were both quicker to learn the association and quicker to realise the switch were the same ones showing more self-control in the first task.

“We found that cuttlefish with better learning performance – an indicator of intelligence – also showed better self-control. This link exists in humans and chimpanzees, but this is the first time it has been shown in a non-primate species,” said Schnell.

The researchers suggest that self-control in cuttlefish is the by-product of another behaviour: staying camouflaged on the sea bed for long periods of time to avoid predators. These periods are punctuated by brief foraging bouts in the open. Self-control may help the cuttlefish optimise their foraging by only striking prey of better quality.

“The ability to exert self-control is an important element of the ability to plan for the future, which is quite a sophisticated behaviour,” said Professor Nicola Clayton FRS in Cambridge’s Department of Psychology, senior author of the report.

She added: “Self-control requires an understanding that ‘less is sometimes more’ – that avoiding temptation now might lead to a better future outcome. This is a critically important building block for the evolution of complex decision-making.”

The researchers also noticed that the cuttlefish in the self-control task turned their bodies away from the immediately available food, as if to distract themselves from eating it.

Self-control – the ability to resist temptation in favour of a better but delayed reward – is a vital skill that underpins effective decision-making, goal-directed behaviour and future planning. Amongst animals, apes and their clever feathered cousins, the corvids and parrots, have relatively high self-control when it comes to eating. Rats, chickens and pigeons find it much more difficult not to eat food immediately.

The experiments were conducted with collaborators including Professor Roger Hanlon at the Marine Biological Laboratory in Woods Hole, Massachusetts. Their design was inspired by the 1972 Stanford marshmallow test, in which children were offered a choice between one marshmallow immediately, or two if they waited for a period of time.

Two additional cuttlefish were recruited to the study but refused to take part.

This research was funded by the Royal Society.

Reference

Schnell, A.K. et al: ‘Cuttlefish exert self-control in a delay of gratification task.’ Proceedings of the Royal Society B, March 2021. DOI: 10.1098/rspb.2020.3161

The researchers, from the University of Cambridge, used modelling and high-speed video techniques to show what causes wheezing and how to predict it. Their results could be used as the basis of a cheaper and faster diagnostic for lung disease that requires just a stethoscope and a microphone.

Improved understanding of the physical mechanism responsible for generating wheezing sounds could provide a better causal link between symptoms and disease, and help improve diagnosis and treatment. The results are reported in the journal Royal Society Open Science.

At some point, most of us have experienced wheezing, a high-pitched whistling sound made while breathing. For most people, the phenomenon is temporary and usually the result a cold or mild allergic reaction. However, regular or chronic wheezing is often a symptom of more serious conditions, such as asthma, emphysema, chronic obstructive pulmonary disease (COPD) or certain cancers.

“Because wheezing makes it harder to breathe, it puts an enormous amount of pressure on the lungs,” said first author Dr Alastair Gregory from Cambridge’s Department of Engineering. “The sounds associated with wheezing have been used to make diagnoses for centuries, but the physical mechanisms responsible for the onset of wheezing are poorly understood, and there is no model for predicting when wheezing will occur.”

Co-author Dr Anurag Agarwal, Head of the Acoustics lab in the Department of Engineering, said he first got the idea to study wheezing after a family vacation several years ago. “I started wheezing the first night we were there, which had never happened to me before,” he said. “And as an engineer who studies acoustics, my first thought was how cool it was that my body was making these noises. After a few days however, I was having real trouble breathing, which made the novelty wear off pretty quickly.”

Agarwal’s wheezing was likely caused by a dust mite allergy, which was easily treated with over-the-counter antihistamines. However, after speaking with a neighbour who is also a specialist in respiratory medicine, he learned that even though it is a common occurrence, the physical mechanisms that cause wheezing are somewhat mysterious.

“Since wheezing is associated with so many conditions, it is difficult to be sure of what is wrong with a patient just based on the wheeze, so we’re working on understanding how wheezing sounds are produced so that diagnoses can be more specific,” said Agarwal.

The airways of the lung are a branching network of flexible tubes, called bronchioles, that gradually get shorter and narrower as they get deeper into the lung.

In order to mimic this setup in the lab, the researchers modified a piece of equipment called a Starling resistor, in which airflow is driven through thin elastic tubes of various lengths and thicknesses.

Co-author and computer vision specialist Professor Joan Lasenby developed a multi-camera stereoscopy technique to film the air being forced through the tubes at different degrees of tension, in order to observe the physical mechanisms that cause wheezing.

“It surprised us just how violent the mechanism of wheezing is,” said Gregory, who is also a Junior Research Fellow at Magdalene College. “We found that there are two conditions for wheezing to occur: the first is that the pressure on the tubes is such that one or more of the bronchioles nearly collapses, and the second is that air is forced though the collapsed airway with enough force to drive oscillations.”

Once these conditions are met, the oscillations grow and are sustained by a flutter mechanism in which waves travelling from front to back have the same frequency as the opening and closing of the tube. “A similar phenomenon has been seen in aircraft wings when they fail, or in bridges when they collapse,” said Agarwal. “When up and down vibrations are at the same frequency as clockwise and anticlockwise twisting vibrations, we get flutter that causes the structure to collapse. The same process is at work inside the respiratory system.”

Using these observations, the researchers developed a ‘tube law’ in order to predict when this potentially damaging oscillation might occur, depending on the tube’s material properties, geometry and the amount of tension.

“We then use this law to build a model that can predict the onset of wheezing and could even be the basis of a cheaper and faster diagnostic for lung disease,” said Gregory. “Instead of expensive and time-consuming methods such as x-rays or MRI, we wouldn’t need anything more than a microphone and a stethoscope.”

A diagnostic based on this method would work by using a microphone – early tests were done using the in-built microphone on a normal smartphone – to record the frequency of the wheezing sound and use this to identify which bronchiole is near collapse, and whether the airways are unusually stiff or flexible in order to target treatment. The researchers hope that by finding changes in material properties from wheezing, and locations that wheezes come from, the additional information will make it easier to distinguish between different conditions, although further work in this area is still needed.

Reference:.
A. L. Gregory, A. Agarwal and J. Lasenby. ‘An Experimental Investigation to Model Wheezing in Lungs.’ Royal Society Open Science (2021). DOI: 10.1098/rsos.201951

By using decades’ worth of data from human motion perception studies, researchers have trained an artificial neural network to estimate the speed and direction of image sequences.

The new system, called MotionNet, is designed to closely match the motion-processing structures inside a human brain. This has allowed the researchers to explore features of human visual processing that cannot be directly measured in the brain.

Their study, published today in the Journal of Vision, uses the artificial system to describe how space and time information is combined in our brain to produce our perceptions, or misperceptions, of moving images.

The brain can be easily fooled. For instance, if there’s a black spot on the left of a screen, which fades while a black spot appears on the right, we will ‘see’ the spot moving from left to right – this is called ‘phi’ motion. But if the spot that appears on the right is white on a dark background, we ‘see’ the spot moving from right to left, in what is known as ‘reverse-phi’ motion.”

The researchers reproduced reverse-phi motion in the MotionNet system, and found that it made the same mistakes in perception as a human brain – but unlike with a human brain, they could look closely at the artificial system to see why this was happening. They found that neurons are ‘tuned’ to the direction of movement, and in MotionNet, ‘reverse-phi’ was triggering neurons tuned to the direction opposite to the actual movement.

The artificial system also revealed new information about this common illusion: the speed of reverse-phi motion is affected by how far apart the dots are, in the reverse to what would be expected. Dots ‘moving’ at a constant speed appear to move faster if spaced a short distance apart, and more slowly if spaced a longer distance apart.

“We’ve known about reverse-phi motion for a long time, but the new model generated a completely new prediction about how we experience it, which no-one has ever looked at or tested before,” said Dr Reuben Rideaux, a researcher in the University of Cambridge’s Department of Psychology and first author of the study.

Humans are reasonably good at working out the speed and direction of a moving object just by looking at it. It’s how we can catch a ball, estimate depth, or decide if it’s safe to cross the road. We do this by processing the changing patterns of light into a perception of motion – but many aspects of how this happens are still not understood.

“It’s very hard to directly measure what’s going on inside the human brain when we perceive motion – even our best medical technology can’t show us the entire system at work. With MotionNet we have complete access,” said Rideaux.

Thinking things are moving at a different speed than they really are can sometimes have catastrophic consequences. For example, people tend to underestimate how fast they are driving in foggy conditions, because dimmer scenery appears to be moving past more slowly than it really is. The researchers showed in a previous study that neurons in our brain are biased towards slow speeds, so when visibility is low they tend to guess that objects are moving more slowly than they actually are.

Revealing more about the reverse-phi illusion is just one example of the way that MotionNet is providing new insights into how we perceive motion. With confidence that the artificial system is solving visual problems in a very similar way to human brains, the researchers hope to fill in many gaps in current understanding of how this part of our brain works.

Predictions from MotionNet will need to be validated in biological experiments, but the researchers say that knowing which part of the brain to focus on will save a lot of time.

Rideaux and his study co-author Dr Andrew Welchman are part of Cambridge’s Adaptive Brain Lab, where a team of researchers is examining the brain mechanisms underlying our ability to perceive the structure of the world around us.

This research was supported by the Leverhulme Trust and the Isaac Newton Trust.

Reference

Rideaux, R. & Welchman, A.E.: ‘Exploring and explaining properties of motion processing in biological brains using a neural network.’ Journal of Vision, Feb 2021. DOI: 10.1167/jov.21.2.11

Around 80% of the UK population is currently infected with human cytomegalovirus (HCMV) and in developing countries this can be as high as 95%. The virus can remain dormant in our white blood cells for decades and, if it reactivates in a healthy individual, does not usually cause symptoms. But, for people who are immunocompromised, HCMV reactivation can be devastating.

HCMV reactivation has been identified in COVID-19 patients, though scientists do not yet understand the relationship between the two viruses. Reactivation or re-infection in transplant recipients can lead to severe illness, including organ rejection and, in some cases, death.

More than 200,000 kidney, lung and stem cell transplants take place globally every year and HCMV reactivation occurs in more than half of these cases. For reasons scientists don’t yet fully understand, immunosuppressants appear to encourage the virus to reactivate as well as compromising the patient’s ability to fight it. There remains no effective vaccine against HCMV and anti-viral therapies often prove ineffective or detrimental.

Now, a team from the University of Cambridge’s School of Clinical Medicine has identified a drug type and treatment strategy that could dramatically reduce these devastating reactivation events. The study, published in the journal PNAS, describes how scientists exposed HCMV-infected blood samples to a wide-range of ‘epigenetic inhibitors’ – drugs widely used in cancer treatment – hoping to prompt the latent virus to produce proteins or targetable antigen that are visible to our immune system.

They discovered that a particular group of these drugs, ‘bromodomain inhibitors’, successfully reactivated the virus by forcing it to convert its hidden genetic instructions into protein. This then enabled T-cells in the blood samples to target and kill these previously undetectable infected cells.

The study is the first to identify the involvement of human host bromodomain (BRD) proteins in the regulation of HCMV latency and reactivation but also proposes a novel ‘shock and kill’ treatment strategy to protect transplant patients.

Lead author Dr Ian Groves said: “We’re looking to purge the patient’s viral reservoir before they go into the operating theatre and before they start taking immunosuppressants, when they would become extremely vulnerable to the virus reactivating. In other words, we’re proposing a pre-emptive strike.

“Prior to transplantation, many patients will have a relatively healthy immune system, so when the virus puts its head above the parapet, its cover is blown, and the immune system will see it and kill the cells it’s been hiding in. Ideally, donors would also be treated to avoid re-infecting recipients.”

There are similar drugs in Phase 1–3 clinical trials around the world for other intended uses, mainly in the treatment of cancers but also Type 2 diabetes-related cardiovascular disease.

Dr Groves said: “This would be the first type of treatment to reduce HCMV infection levels pre-transplant in order to lower the chances of virus reactivation during immune suppression after transplantation. Our findings could lead to thousands of lives being saved every year.”

“In addition to the terrible human suffering this virus causes, treating its effects adds enormously to the high costs already incurred by transplantation. It’s a really serious issue for health services in wealthy nations and a desperate one in developing countries. Our findings offer an opportunity to transform this horrible situation.”

The study builds on over 25 years of extensive research into the molecular biology of HCMV and its immune evasion tactics (funded by the Medical Research Council). The researchers hope their study could eventually help doctors fight HCMV on other fronts, including in maternity and neo-natal care. HCMV affects at least 1% of all live births in developed countries, and many more in developing countries. These children can be left with brain damage and hearing loss, but congenital infection during pregnancy can also lead to miscarriage.

Reference

I. J. Groves et al., ‘Bromodomain proteins regulate human cytomegalovirus latency and reactivation allowing epigenetic therapeutic intervention’. PNAS (2021). DOI: 10.1073/pnas.2023025118

The JUNIPER consortium (‘Joint UNIversities Pandemic and Epidemiological Research’) brings together leading mathematical and statistical modellers from seven UK universities and has received £3 million in funding from UK Research and Innovation (UKRI).

JUNIPER is developing and using customised models to provide predictions and estimates on key questions about the COVID-19 pandemic. These results feed regularly into SPI-M, the modelling group that provides evidence to the Scientific Advisory Group for Emergencies (SAGE) and the wider UK government.

Examples of modelling JUNIPER provides to government includes:

• Understanding how new variants are spreading across the UK and developing statistical models to determine whether new variants are causing more hospitalisations or deaths.
• Forecasting and providing real-time estimates of the R-value, using data from sources such as Pillar 1 and 2 testing, hospital data and mobility data. They are currently providing eight of 12 models contributing real-time R estimates that go from SPI-M to SAGE each week.
• Modelling the effectiveness of different testing strategies on virus transmission and suppression, and modelling the effect of vaccinations and predicting outcomes from different scenarios of how to ease lockdown restrictions.

Professor Julia Gog, co-lead of the consortium from Cambridge’s Department of Applied Mathematics and Theoretical Physics, said: “By bringing research groups together from our seven universities we can provide predictions and estimates about the pandemic to address questions from the government with unprecedented speed. By combining the right expertise together swiftly across research teams we can now respond to questions in less than 24 hours, which might have taken a week for one team working alone. And further, being able to call upon specialist expertise combinations across multiple research groups means we can provide more robust outputs.

“In this unprecedented pandemic, modelling has been hugely important to provide evidence-based predictions and estimates at great speed. Our insights from transmission modelling are fully integrated with scientific evidence from other disciplines and feed into government decision-making.”

Professor Matt Keeling, co-lead of the consortium from the University of Warwick, said: “We’re generating about half the models for the nowcasting that goes into SPI-M and SAGE every week. This consortium allows us to not only boost our speed and capacity, but also to continue to advance the accuracy of our models using the new data and growing knowledge from the pandemic.

“Standard epidemiological modelling tools have worked well so far, but the future with COVID-19 now demands a suite of new tools to deal with the upcoming complexities of the pandemic, such as localised regional outbreaks, growing understanding of socioeconomic differences with this disease, complexities of imperfect vaccines and the growing problem ahead with new variants. Having several teams using different models working on the same problem helps us to verify our results and makes the consortium much bigger than the sum of its parts.”

The consortium is funded as part of UKRI’s COVID-19 Agile Call, which has so far invested more than £150M in over 400 projects to address the impacts of the COVID-19 pandemic.

Professor Charlotte Deane, COVID-19 Response Director at UKRI, said: “This consortium enables disease modellers to pool their expertise nationally to increase the scale, speed and quality of their models of policy options and predictions for the pandemic. They’ll provide cutting-edge evidence about the pandemic into the UK government’s decision-making.”

The consortium will also proactively generate new model-based predictions and develop the necessary methodology as part of a horizon-scanning process.

The consortium plan to make their models open-source, so scientists worldwide can access them and benefit.

The seven universities involved in JUNIPER are Cambridge, Warwick, Exeter, Oxford, Bristol, Manchester and Lancaster Universities.

They will work closely with other organisations and research teams active on COVID-19 research including the Alan Turing Institute, the Royal Statistical Society, Health Data Research UK, Public Health England, the Royal Society’s ‘RAMP’ initiative, and the Isaac Newton Institute for Mathematical Sciences.

The UK’s first national lockdown from March 2020 and its immediate aftermath saw a massive shift in consumer habits that was initially mandated but then lingered as shops and restaurants opened but risks from the virus remained.

A new study from the universities of Cambridge and Newcastle used data from the ONS to compare retail, hospitality and online sales in the UK between March and August 2020 with average figures for the same months for the years 2010-2019.

Researchers took an approach normally used to estimate cumulative excess deaths to try and measure the impact of the COVID-19 shock on sales of UK retailers and restaurants.

They say their economic models suggest that shops predominantly selling food, such as supermarkets, saw a 5-10% bump in sales in lockdown, adding up to an additional £4 billion in earnings over “business as usual” expectations.

This is “consistent with large-scale stockpiling”, they say, as people prepared for an indefinite future of home-cooked meals.

With many shops shut and people stuck indoors, online sales experienced a major boost, peaking at around a third higher than business-as-usual estimates during the first lockdown – an increase that amounts to an additional £4 billion.

Non-food high street shops, those selling everything from books to clothes, saw sales evaporate during the first lockdown when they had to shut, costing around £20 billion in turnover. Sales returned to normal once national lockdown lifted.

The shortfall for bars, pubs and restaurants was “dramatic”, say researchers, with the first UK lockdown causing sales to fall as much as 90% below the business-as-usual level, equating to around a £25 billion revenue loss.

Hospitality sales saw some recovery post-lockdown, as government schemes such as ‘Eat Out to Help Out’ kicked in, but were still 25% below estimated business-as-usual revenues by the end of summer.

Writing in the journal Global Food Security, researchers say they found no evidence of a post-lockdown fall in food-shop sales as people used up their stockpiles, or an “overshoot” on the high street due to “pent-up demand” during lockdown.

“Lockdown restrictions led to behaviour changes in consumers and retailers that caused huge fluctuations in sales,” said Dr Shaun Larcom from the University of Cambridge, who co-authored the study with his Cambridge colleague Dr Po-Wen She and Dr Luca Panzone from the Newcastle University.

“Shopping frequency dramatically reduced, and footfall vanished from many commercial areas, with people going online or using local outlets within residential areas when they had to shop.”

“Consequences of lockdown, such as long queues outside supermarkets, led to ‘forced experimentation’. Consumers had to explore new purchasing methods,” said Larcom, from Cambridge’s Department of Land Economy.

“Many people shopped online for the first time. They also bought directly from wholesalers or even farms, and trialled different types of home cooking. When people are forced to experiment, it can lead to behaviour changes that last well beyond the life of a crisis.”

The researcher say that, while online sales peaked during lockdown, they remained above pre-lockdown levels in August 2020, which they suggest may be early signs of a more permanent “structural change” in shopping habits.

Recent media reports suggest that the UK Treasury is considering a one-off tax for online retailers who saw profits boosted by the lockdowns.

In February 2020, stores primarily selling food had sales figures almost identical to business-as-usual (BAU) estimates produced by the researchers’ econometric models: £12.6 billion. Sales for March ran at £17.5 billion – around 10% higher than the £16 billion BAU estimates – but had returned to BAU levels by July.

For online retail, sales sharply diverged from BAU estimates by May – £5.3 billion against a predicted value of £4.1 billion (+29%) – and peaked in June at £6.8 billion compared to £5 billion BAU estimate (+36%). While online sales then started to fall, they were still above BAU estimates by the end of summer.

Non-food shops had February sales figures almost equal to their BAU estimates: £11.6 and £11.9 billion respectively. Actual sales tumbled as the pandemic took hold, with an April nadir of £5.9 billion compared to BAU estimates of £13 billion (-54.6%). Sales then started to recover, and by August only just lagged BAU estimates.

Sales in “food and beverage serving services” suffered most in terms of lost revenue. In February, turnover was £5.7 billion, just shy of the £6 billion BAU estimate. By March this had slumped to £4.3 billion against a prediction of £6.7 billion.

April sales for bars, pubs and restaurants were just £0.7 billion compared to a BAU estimate of £6.7 billion: an approximate shortfall of 90%. While this gap shrank it remained startling. Even with the ‘Eat Out to Help Out’ scheme, August sales were £5.2 billion compared to a BAU estimate of £7 billon (-25%).

“Understanding the monetary impact of the pandemic is important to gauge the magnitude of the damage, and can help government design policies to assist these sectors,” said Panzone from the University of Newcastle.

“Food services and non-food retailers lost a huge share of their yearly business, compared to food stores and online retailers that actually gained from lockdown. One-size-fits-all policy approaches across retail won’t work,” he said.

A team at Cambridge’s School of Medicine carried out a systematic review looking at the existing evidence on different approaches to tackling loneliness and social isolation. While all the individual studies were carried out pre-pandemic, the team considered which approaches might be feasible when people are still required to socially distance. Their results are published today in PLOS ONE.

At the start of the pandemic in the UK, over 1.5 million people were told they must self-isolate or shield themselves for a period of at least 12 weeks. Strict social distancing guidance advised the public to stop all non-essential travel and stay at home. While these measures were initially eased, social distancing measures remain in place, cases and contacts are required to self-isolate, and further lockdown measures have been re-introduced.

One possible consequence of both the shielding of vulnerable people, and the social distancing restrictions for all, is for physical separation to lead to social isolation and loneliness. There is strong evidence that both social isolation and loneliness are linked to cardiovascular disease, depression and anxiety. This means there is an urgent need to identify effective interventions to combat this problem.

A team led by Dr Christopher Williams, at the time University of Cambridge medical student, identified 58 relevant studies of interventions to reduce social isolation, social support and loneliness that could potentially be adapted for people living in pandemic-related isolation. Most of the studies (51 out of 58) related to older people – a group that often face the strictest limitations imposed on their social contacts during the pandemic.

“Lockdown and social distancing measures have meant that many people have little or no contact with others, which can lead to loneliness and isolation,” said Dr Williams, now a doctor in his first year of practice.

“We carried out our review to try and identify approaches that might help people cope with these challenging times. Although the individual studies themselves took place before the pandemic, we’ve identified several that would still be feasible even with social distancing measures in place.”

Among some of the approaches identified in the studies are:

• Robot dogs and robot seals (but not real budgies): Two studies indicated that robotic dogs could prove as effective as real dogs in reducing loneliness. They might also be more feasible for some groups living in pandemic conditions than real dogs. Similarly, weekly sessions with Paro, an interactive robotic seal that responds to contact and other stimuli by moving or imitating the noises of a baby harp seal, significantly improved loneliness scores. The robotic animals gave better results than an ‘avian companionship’ scheme involving interacting with a live budgie, which did not report significant results.
• Mindfulness and Tai Chi: Mindfulness-based therapies and Tai Chi Qigong meditation led to significant improvements in loneliness or social support outcomes.
• Laughter therapy: Laughter exercises, deep breathing exercises, playing games, singing songs loudly and laughter meditation also helped reduce loneliness. Together with mindfulness and Tai Chi Qigong meditation, these represent potentially low-cost interventions that can be conducted in online groups on a large scale.
• Talking about art: Visual art discussions – where participants were asked to describe a painting, to use their imagination to describe why, how and when it was made, and to describe associations that appear when looking at the painting such as feelings, memories and thoughts – demonstrated significant improvements in loneliness or social support outcomes.
• Reminiscence therapy: Structured weekly sessions concentrated on a different topic each week, including sharing memories, increasing participant awareness/expression of their feelings, identifying past positive relationships, recalling family history and life stories, and identifying positive strengths and goals.
• Lessons on friendship and social integration: Educational programme interventions varied, with some focusing on theories of loneliness and social integration while others sought to educate on health and well-being more generally. Lessons on friendship and social integration typically decreased loneliness, with three out of four studies showing improvement.
• Wii gaming: Playing games such as Wii Sports and Cooking Mama on the Wii console were found to be effective at reducing loneliness. However, the studies involved group play, which would only be feasible in support bubbles during lockdown – it is not clear whether the same benefits would be seen from online play.
• Indoor gardening: One study of an indoor gardening programme in a nursing home, where participants were given their own plants and taught how to look after them, reported decreased loneliness scores among participants of the programme and increased participants’ social networks.
• Get to know your neighbours: Group meetings between participants in the same neighbourhood, discussing the residential area, the role of retiree, social and medical services, and opportunities for leisure activities, reduced social isolation, though they did not significantly alter loneliness levels.
• Video conferencing: Two studies looking at video calls found that weekly catch-ups with family members could help reduce feelings of loneliness.

The majority of the studies improved loneliness. The little evidence found by the team on tackling social isolation suggests that enabling or encouraging people to interact with their existing social circles was more effective than trying to enable them to make new friends.

“Many of these activities, such as mindfulness, meditation and talking therapies, could be delivered at a large scale in online groups, potentially at low cost,” said Dr Adam Townson from School of Clinical Medicine at Cambridge.

“A significant problem, however, is that those who are most likely to be lonely or isolated – and most in need of support – may not own, or know how to use, electronic devices and might not have access to a high-speed internet connection. Any approach to help people suffering from loneliness or social isolation must take digital exclusion into consideration.”

Several studies involved initiatives to combat loneliness and social isolation in nursing and care homes, which may have been hit particularly hard by lockdown measures. Effective interventions in these settings included weekly visits from an interactive robotic dog or seal, Wii gaming, gardening, videoconferencing, and cognitive/psychological interventions.

The UK Government has announced a £5 million Loneliness COVID-19 Grant Fund to support charities currently offering services such as telephone befriending and community volunteering schemes. In addition, the NHS.uk website provides both support for people feeling lonely and onward referral for psychological therapies if appropriate. The researchers hope that their findings could help inform these national efforts.

The research was supported by the National Institute for Health Research.

Reference
Williams, C, et al. Interventions to reduce social isolation and loneliness during COVID-19 physical distancing measures: A rapid systematic review. PLOS ONE; 17 Feb 2021; DOI: 10.1371/journal.pone.0247139

The researchers, from the University of Cambridge, were able to inject a ‘needle’ of highly fragile quantum information in a ‘haystack’ of 100,000 nuclei. Using lasers to control an electron, the researchers could then use that electron to control the behaviour of the haystack, making it easier to find the needle. They were able to detect the ‘needle’ with a precision of 1.9 parts per million: high enough to detect a single quantum bit in this large ensemble.

The technique makes it possible to send highly fragile quantum information optically to a nuclear system for storage, and to verify its imprint with minimal disturbance, an important step in the development of a quantum internet based on quantum light sources. The results are reported in the journal Nature Physics.

The first quantum computers – which will harness the strange behaviour of subatomic particles to far outperform even the most powerful supercomputers – are on the horizon. However, leveraging their full potential will require a way to network them: a quantum internet. Channels of light that transmit quantum information are promising candidates for a quantum internet, and currently there is no better quantum light source than the semiconductor quantum dot: tiny crystals that are essentially artificial atoms.

However, one thing stands in the way of quantum dots and a quantum internet: the ability to store quantum information temporarily at staging posts along the network.

“The solution to this problem is to store the fragile quantum information by hiding it in the cloud of 100,000 atomic nuclei that each quantum dot contains, like a needle in a haystack,” said Professor Mete Atatüre from Cambridge’s Cavendish Laboratory, who led the research. “But if we try to communicate with these nuclei like we communicate with bits, they tend to ‘flip’ randomly, creating a noisy system.”

The cloud of quantum bits contained in a quantum dot don’t normally act in a collective state, making it a challenge to get information in or out of them. However, Atatüre and his colleagues showed in 2019 that when cooled to ultra-low temperatures also using light, these nuclei can be made to do ‘quantum dances’ in unison, significantly reducing the amount of noise in the system.

Now, they have shown another fundamental step towards storing and retrieving quantum information in the nuclei. By controlling the collective state of the 100,000 nuclei, they were able to detect the existence of the quantum information as a ‘flipped quantum bit’ at an ultra-high precision of 1.9 parts per million: enough to see a single bit flip in the cloud of nuclei.

“Technically this is extremely demanding,” said Atatüre, who is also a Fellow of St John’s College. “We don’t have a way of ‘talking’ to the cloud and the cloud doesn’t have a way of talking to us. But what we can talk to is an electron: we can communicate with it sort of like a dog that herds sheep.”

Using the light from a laser, the researchers are able to communicate with an electron, which then communicates with the spins, or inherent angular momentum, of the nuclei.

By talking to the electron, the chaotic ensemble of spins starts to cool down and rally around the shepherding electron; out of this more ordered state, the electron can create spin waves in the nuclei.

“If we imagine our cloud of spins as a herd of 100,000 sheep moving randomly, one sheep suddenly changing direction is hard to see,” said Atatüre. “But if the entire herd is moving as a well-defined wave, then a single sheep changing direction becomes highly noticeable.”

In other words, injecting a spin wave made of a single nuclear spin flip into the ensemble makes it easier to detect a single nuclear spin flip among 100,000 nuclear spins.

Using this technique, the researchers are able to send information to the quantum bit and ‘listen in’ on what the spins are saying with minimal disturbance, down to the fundamental limit set by quantum mechanics.

“Having harnessed this control and sensing capability over this large ensemble of nuclei, our next step will be to demonstrate the storage and retrieval of an arbitrary quantum bit from the nuclear spin register,” said co-first author Daniel Jackson, a PhD student at the Cavendish Laboratory.

“This step will complete a quantum memory connected to light – a major building block on the road to realising the quantum internet,” said co-first author Dorian Gangloff, a Research Fellow at St John’s College.

Besides its potential usage for a future quantum internet, the technique could also be useful in the development of solid-state quantum computing.

The research was supported in part by the European Research Council (ERC), the Engineering and Physical Sciences Research Council (EPSRC) and the Royal Society.

Reference:
D. M. Jackson et al. ‘Quantum sensing of a coherent single spin excitation in a nuclear ensemble.’ Nature Physics (2021). DOI: 10.1038/s41567-020-01161-4

The researchers, from the University of Cambridge, carried out a series of different fit tests, and found that when a high-performance mask – such as an N95, KN95 or FFP2 mask – is not properly fitted, it performs no better than a cloth mask. Minor differences in facial features, such as the amount of fat under the skin, make significant differences in how well a mask fits.

The results, published in the journal PLoS ONE, also suggest that the fit-check routine used in many healthcare settings has high failure rates, as minor leaks may be difficult or impossible to detect by the wearer. While the sample size was small, the researchers hope their findings will help develop new fit tests that are quick and reliable, in the case of future public health emergencies. The current study only evaluated the impact of fit on the wearer of the mask – the team will evaluate how fit impacts the protection of others in future research.

The COVID-19 pandemic has made well-fitting face masks a vital piece of protective equipment for healthcare workers and civilians. While the importance of wearing face masks in slowing the spread of the virus has been demonstrated, there remains a lack of understanding about the role that good fit plays in ensuring their effectiveness.

“We know that unless there is a good seal between the mask and the wearer’s face, many aerosols and droplets will leak through the top and sides of the mask, as many people who wear glasses will be well aware of,” said Eugenia O’Kelly from Cambridge’s Department of Engineering, the paper’s first author. “We wanted to quantitatively evaluate the level of fit offered by various types of masks, and most importantly, assess the accuracy of implementing fit-checks by comparing fit-check results to quantitative fit testing results.”

For the study, seven participants first evaluated N95 and KN95 masks by performing a fit check, according to NHS guidelines. Participants then underwent quantitative fit testing – which uses a particle counter to measure the concentration of particles inside and outside the mask – while wearing N95 and KN95 masks, surgical masks, and fabric masks. The results assessed the protection to the mask wearer, which is important in clinical settings.

N95 masks – which are a similar standard to the FFP3 masks available in the UK and the rest of Europe – offered higher degrees of protection than the other categories of masks tested; however, most N95 masks failed to fit the participants adequately.

In their study, the researchers found that when fitted properly, N95 masks filtered more than 95% of airborne particles, offering superior protection. However, in some cases, poorly-fitted N95 masks were only comparable with surgical or cloth masks.

“It’s not enough to assume that any single N95 model will fit the majority of a population,” said O’Kelly. “The most widely-fitting mask we looked at, the 8511 N95, fit only three out of the seven participants in our study.”

One observation the researchers made during their study was the width of the flange of the mask – the area of the material which comes in contact with the skin – may be a critical feature to fit. Masks which fit the greatest number of participants tended to have wider, more flexible flanges around the border.

In addition, small facial differences were observed to have a significant impact on quantitative fit. “Fitting the face perfectly is a difficult technical challenge and, as our research showed, small differences such as a centimetre wider nose or slightly fuller cheeks can make or break the fit of a mask,” said O’Kelly.

Self-performed fit-checks are attractive because they save on time and resources, and are often the only method of fit testing available. However, this study, and studies of fit-check systems in other countries, indicate that such fit-check systems are not reliable.

The researchers hope that their results will be of use for those who are working on new technologies and programmes to assess fit, so that healthcare and other frontline workers are adequately protected in the case of any future pandemics. Additionally, they hope these results will bring attention to the importance of fit in clinical-grade masks, especially if such masks are to be widely used by the public.  This study did not evaluate the impact of fit on protecting others, which is a future area of research.

Reference:
Eugenia O’Kelly et al. ‘Comparing the fit of N95, KN95, surgical, and cloth face masks and assessing the accuracy of fit checking.’ PLoS ONE (2021). DOI: 10.1371/journal.pone.0245688

A study published in Nature Communications presents new evidence about what a key protein called alpha-synuclein actually does in neurons in the brain.

Dr Giuliana Fusco from the University of Cambridge, and lead author of the paper, said: “This study could unlock more information about this debilitating neurodegenerative disorder that can leave people unable to walk and talk. If we want to cure Parkinson’s, first we need to understand the function of alpha-synuclein, a protein present in everyone’s brains. This research is a vital step towards that goal.”

Parkinson’s disease is a progressive neurological disorder that causes nerve cells in the brain to weaken or die. The disease has a variety of symptoms including tremors – particularly in the hands – gait and balance problems, slowness and extreme stiffness in the arms and legs. Parkinson’s develops when cells in the brain stop working properly and can’t produce enough dopamine, a chemical that controls movement in the body by acting as a messenger between cells.

The disease mostly affects people over 60 and gets worse over a number of years but early-onset Parkinson’s can affect people even younger.

More than 10 million people worldwide live with Parkinson’s disease including actor Michael J. Fox who was diagnosed aged 29, singer Neil Diamond, comedian Billy Connolly and musician Ozzy Osbourne. Parkinson’s can affect women, but men are more likely to have the disease.

It is not yet known why people get Parkinson’s, but researchers think it’s a combination of age, genetic and environmental factors that cause the dopamine-producing nerve cells to die affecting the body’s ability to move.

The new study looked at what was going on inside healthy conditions to help pinpoint what is going wrong in the cells of people with Parkinson’s. All cells in the body have a plasma membrane that protects cells and usually transports nutrients in and clears toxic substances out.

“One of the top questions in Parkinson’s research is: what is the function of alpha-synuclein, the protein that under pathological conditions forms clumps that affect motor and cognitive abilities,” said Fusco, who is also a research Fellow at St John’s College, Cambridge. “Usually you discover a protein for its function and then you explore what is going wrong when disease strikes, in the case of alpha-synuclein the protein was identified for its pathological association but we didn’t know what it did in the neuron.

“Our research suggests that the alpha-synuclein protein sticks like glue to the inner face of the plasma membrane of nerve cells but not to the outer– a crucial new piece of information.”

The research was predominantly carried out at the Cambridge for Misfolding Diseases at the University of Cambridge. The scientists used synthetic models to mimic brain cell membranes during the study.

“When this protein is functioning normally it plays an important part in the mechanisms by which neurons exchange signals in the brain,” said co-author Professor Alfonso De Simone, from Imperial College London. “But it has a dark side because it malfunctions and begins to stick together in clumps which eventually spread and kill healthy brain cells. Our research showed that this protein clings onto the inner face of the plasma membrane of brain cells so we are slowly building a picture of this very complex disorder by studying the key function of alpha-synuclein.”

There are treatments and drugs available to Parkinson’s patients and the disease isn’t fatal, but nothing is available to reverse the effects of the disease. Introducing lifestyle changes including getting more rest and exercise can also alleviate symptoms.

De Simone said: “We have thousands of proteins in our bodies and until the function of this mystery protein is confirmed with more research, drug therapies cannot begin to be developed to tackle the origins of Parkinson’s Disease in case medication accidentally affect a crucial purpose of the alpha-synuclein protein.”

Reference:
Wing K. Man et al. ‘The docking of synaptic vesicles on the presynaptic membrane induced by α-synuclein is modulated by lipid composition.’ Nature Communications (2021). DOI: 10.1038/s41467-021-21027-4

Adapted from a St John’s College press release.

The University of Cambridge report, which was commissioned by the Foreign, Commonwealth and Development Office, argues that there is an urgent need to do more to support marginalised, adolescent women in low and middle-income countries; many of whom leave education early and then face an ongoing struggle to build secure livelihoods.

Amid extensive evidence which highlights the difficulties these women face, it estimates that almost a third of adolescent women in many such countries are not in education, training, or work.

‘Adolescents’ (technically people aged 10 to 19) comprise about one sixth of the world’s population. Women in this age group are some of the most vulnerable people in the world. The report argues that unless more is done to support them, it is unlikely that the UN’s 2030 Sustainable Development Goals – which include ending poverty, ensuring inclusive education, and empowering women and girls – will be met.

In particular, the document highlights the need for more concerted efforts to be made to prevent gender discrimination in labour markets, strengthen social safety nets for women, and provide both formal education and continued training for the huge numbers of adolescent women who, it says, ‘have missed out on acquiring relevant skills to enhance their livelihood opportunities.’

Professor Pauline Rose, Director of the Research for Equitable Access and Learning (REAL) Centre at the Faculty of Education, University of Cambridge, said: “Marginalised adolescent girls are those who experience extreme poverty, live in rural areas, have disabilities, are affected by conflict, or belong to disadvantaged groups. We need to prioritise these young women both in education and as they transition into work. Millions are being left behind by a range of interlocking problems, and strong, sustained political leadership is needed to turn that around.”

The Government has identified girls’ education as a key focus of the UK’s presidency of the G7 group of industrial countries this year, and gender equality will be mainstreamed across the different ministerial tracks. The new report raises gender inequality – both in education and employment – as major areas of concern for the international community.

The report further stresses that adolescence is a make-or-break time for many girls in low- and lower-middle-income countries and should therefore be a focal point of international efforts. During this period, many young women leave education early, either to work, or because they are expected to marry and start a family. Often, they do so without having acquired basic literacy or numeracy. In addition, very few have the transferable skills or training that they need to succeed in the world of work.

The document draws on more than 150 sources to evidence both the scale of the problem and the nature of the barriers that marginalised adolescent girls face. For many, a quality education remains a far-off dream. In sub-Saharan Africa, for example, fewer than one in 10 girls from poor households in rural areas complete lower secondary education.

Many also struggle to find secure employment. Data from 30 low- and middle-income countries suggests that 31% of young women are not in education, employment or training, compared with 16% of boys. Those who do find jobs frequently work for low wages, in unsafe settings and without any sort of social safety net.

One of the main reasons for this, the report says, is a lack of access to appropriate skills development and training. For example, one in three unemployed adolescent girls in the Asia-Pacific region, and one in five in sub-Saharan Africa, report that the entry requirements for their preferred career path exceed their education and training.

Compounding these problems, gender discrimination in both labour markets and wider society is an accepted norm in many countries. Among many other examples, this manifests itself in inheritance laws which transfer land and property to sons but not daughters; the tendency to force girls who struggle to find work into early marriage and childbearing; and widespread gender-related violence. One study in Nigeria, cited in the report, found that two-thirds of young female apprentices had experienced physical violence – and 39% said that their employer was the most recent perpetrator.

While the research also identifies many successful individual programmes around the world that address some of these issues, it stresses the need for policy-makers internationally to prioritise adolescent girls in larger-scale, systemic reforms.

It makes numerous recommendations about how that can be done, including:

• Implementing measures and laws that challenge gender discrimination in education, labour markets and wider society.
• Curriculum reforms to develop women’s transferrable skills in school, supported by skills development programmes outside the education system.
• Catch-up programmes for those who have missed out on a basic education.
• Strengthening social safety nets, which have been shown to benefit women in particular.
• Providing sexual and reproductive health services and information for all adolescent girls.
• Providing counselling and rehabilitation services that offer practical support to adolescent girls who have been forced into unsafe work settings.

The report highlights the particular role that female political leaders and parliamentarians can play in driving forward a more integrated agenda for marginalised young women, and in challenging patriarchal norms that hold back gender equality.

It also warns that many of the trends documented are currently at risk of becoming worse as a result of COVID-19. “The best way that Governments can signal their commitment to this problem is by putting women and girls at the forefront of COVID-19 recovery efforts and ambitions to build back better,” Rose said. “It is vital that this includes a strong focus on adolescent girls.”

The researchers, from the University of Cambridge, used their method to culture and grow a ‘mini-airway’, the first time that a tube-shaped organoid has been developed without the need for any external support.

Using a mould made of a specialised polymer, the researchers were able to guide the size and shape of the mini-airway, grown from adult mouse stem cells, and then remove it from the mould when it reached the point where it could support itself.

Whereas the organoids currently used in medical research are at the microscopic scale, the method developed by the Cambridge team could make it possible to grow life-sized versions of organs. Their results are reported in the journal Advanced Science.

Organoids are tiny, three-dimensional cell assemblies that mimic the cell arrangement of fully-grown organs. They can be a useful way to study human biology and how it can go wrong in various diseases, and possibly how to develop personalised or regenerative treatments. However, assembling them into larger organ structures remains a challenge.

Other research teams have experimented with 3D printing techniques to develop larger mini-organs, but these often require an external support structure.

“Mini-organs are very small and highly fragile,” said Dr Yan Yan Shery Huang from Cambridge’s Department of Engineering, who co-led the research. “In order to scale them up, which would increase their usefulness in medical research, we need to find the right conditions to help the cells self-organise.”

Huang and her colleagues have proposed a new organoid engineering approach called Multi-Organoid Patterning and Fusion (MOrPF) to grow a miniature version of a mouse airway using stem cells. Using this technique, the scientists achieved faster assembly of organoids into airway tubes with uninterrupted passageways. The mini-airways grown using the MOrPF technique showed potential for scaling up to match living organ structures in size and shape, and retained their shape even in the absence of an external support.

The MOrPF technique involves several steps. First, a polymer mould – like a miniature version of a cake or jelly mould – is used to shape a cluster of many small organoids. The cluster is released from the mould after one day, and then grown for a further two weeks. The cluster becomes one single tubular structure, covered by an outer layer of airway cells. The moulding process is just long enough for the outer layer of the cells to form an envelope around the entire cluster. During the two weeks of further growth, the inner walls gradually disappear, leading to a hollow tubular structure.

“Gradual maturation of the cells is really important,” said Dr Joo-Hyeon Lee from Cambridge’s Wellcome – MRC Cambridge Stem Cell Institute, who co-led the research. “The cells need to be well-organised before we can release them so that the structures don’t collapse.”

The organoid cluster can be thought of like soap bubbles, initially packed together to form to the shape of the mould. In order to fuse into a single gigantic bubble from the cluster of compressed bubbles, the inner walls need to be broken down. In the MOrPF process, the fused organoid clusters are released from the mould to grow in floating, scaffold-free conditions, so that the cells forming the inner walls of the fused cluster can be taken out of the cluster. The mould can be made into different sizes or shapes, so that the researchers can pre-determine the shape of the finished mini-organ.

“The interesting thing is, if you think about the soap bubbles, the resulting big bubble is always spherical, but the special mechanical properties of the cell membrane of organoids make the resulting fused shape preserve the shape of the mould,” said co-author Professor Eugene Terentjev from Cambridge’s Cavendish Laboratory.

The team say their method closely approximated the natural process of organ tube formation in some animal species. They are hopeful that their technique will help create biomimetic organs to facilitate medical research.

The researchers first plan to use their method to build a three-dimensional ‘organ on a chip’, which enables real-time continuous monitoring of cells, and could be used to develop new treatments for disease while reducing the number of animals used in research. Eventually, the technique could also be used with stem cells taken from a patient, in order to develop personalised treatments in future.

The research was supported in part by the European Research Council, the Wellcome Trust and the Royal Society.

Reference:
Ye Liu et al. ‘Bio-assembling Macro-Scale, Lumenized Airway Tubes of Defined Shape via Multi-Organoid Patterning and Fusion.’ Advanced Science (2021). DOI: 10.1002/advs.202003332

The researchers, led by the University of Cambridge, were able to control the conductivity and magnetism of iron thiophosphate (FePS₃), a two-dimensional material which undergoes a transition from an insulator to a metal when compressed. This class of magnetic materials offers new routes to understanding the physics of new magnetic states and superconductivity.

Using new high-pressure techniques, the researchers have shown what happens to magnetic graphene during the transition from insulator to conductor and into its unconventional metallic state, realised only under ultra-high pressure conditions. When the material becomes metallic, it remains magnetic, which is contrary to previous results and provides clues as to how the electrical conduction in the metallic phase works. The newly discovered high-pressure magnetic phase likely forms a precursor to superconductivity so understanding its mechanisms is vital.

Their results, published in the journal Physical Review X, also suggest a way that new materials could be engineered to have combined conduction and magnetic properties, which could be useful in the development of new technologies such as spintronics, which could transform the way in which computers process information.

Properties of matter can alter dramatically with changing dimensionality. For example, graphene, carbon nanotubes, graphite and diamond are all made of carbon atoms, but have very different properties due to their different structure and dimensionality.

“But imagine if you were also able to change all of these properties by adding magnetism,” said first author Dr Matthew Coak, who is jointly based at Cambridge’s Cavendish Laboratory and the University of Warwick. “A material which could be mechanically flexible and form a new kind of circuit to store information and perform computation. This is why these materials are so interesting, and because they drastically change their properties when put under pressure so we can control their behaviour.”

In a previous study by Sebastian Haines of the Cavendish Laboratory and the Department of Earth Sciences, researchers established that the material becomes a metal at high pressure, and outlined how the crystal structure and arrangement of atoms in the layers of this 2D material change through the transition.

“The missing piece has remained however, the magnetism,” said Coak. “With no experimental techniques able to probe the signatures of magnetism in this material at pressures this high, our international team had to develop and test our own new techniques to make it possible.”

The researchers used new techniques to measure the magnetic structure up to record-breaking high pressures, using specially designed diamond anvils and neutrons to act as the probe of magnetism. They were then able to follow the evolution of the magnetism into the metallic state.

“To our surprise, we found that the magnetism survives and is in some ways strengthened,” co-author Dr Siddharth Saxena, group leader at the Cavendish Laboratory. “This is unexpected, as the newly-freely-roaming electrons in a newly conducting material can no longer be locked to their parent iron atoms, generating magnetic moments there – unless the conduction is coming from an unexpected source.”

In their previous paper, the researchers showed these electrons were ‘frozen’ in a sense. But when they made them flow or move, they started interacting more and more. The magnetism survives, but gets modified into new forms, giving rise to new quantum properties in a new type of magnetic metal.

How a material behaves, whether conductor or insulator, is mostly based on how the electrons, or charge, move around. However, the ‘spin’ of the electrons has been shown to be the source of magnetism. Spin makes electrons behave a bit like tiny bar magnets and point a certain way. Magnetism from the arrangement of electron spins is used in most memory devices: harnessing and controlling it is important for developing new technologies such as spintronics, which could transform the way in which computers process information.

“The combination of the two, the charge and the spin, is key to how this material behaves,” said co-author Dr David Jarvis from the Institut Laue-Langevin, France, who carried out this work as the basis of his PhD studies at the Cavendish Laboratory. “Finding this sort of quantum multi-functionality is another leap forward in the study of these materials.”

“We don’t know exactly what’s happening at the quantum level, but at the same time, we can manipulate it,” said Saxena. “It’s like those famous ‘unknown unknowns’: we’ve opened up a new door to properties of quantum information, but we don’t yet know what those properties might be.”

There are more potential chemical compounds to synthesise than could ever be fully explored and characterised. But by carefully selecting and tuning materials with special properties, it is possible to show the way towards the creation of compounds and systems, but without having to apply huge amounts of pressure.

Additionally, gaining fundamental understanding of phenomena such as low-dimensional magnetism and superconductivity allows researchers to make the next leaps in materials science and engineering, with particular potential in energy efficiency, generation and storage.

As for the case of magnetic graphene, the researchers next plan to continue the search for superconductivity within this unique material. “Now that we have some idea what happens to this material at high pressure, we can make some predictions about what might happen if we try to tune its properties through adding free electrons by compressing it further,” said Coak.

“The thing we’re chasing is superconductivity,” said Saxena. “If we can find a type of superconductivity that’s related to magnetism in a two-dimensional material, it could give us a shot at solving a problem that’s gone back decades.”

Reference:
Matthew J. Coak et al. ‘Emergent Magnetic Phases in Pressure-Tuned van der Waals Antiferromagnet FePS3.’ Physical Review X (2021). DOI: 10.1103/PhysRevX.11.011024