Rare disease research at Cambridge receives major boost with launch of two new centres
The virtual centres, supported by the charity LifeArc, will focus on areas where there are significant unmet needs. They will tackle barriers that ordinarily prevent new tests and treatments reaching patients with rare diseases and speed up the delivery of rare disease treatment trials.
The centres will bring together leading scientists and rare disease clinical specialists from across the UK for the first time, encouraging new collaborations across different research disciplines and providing improved access to facilities and training.
LifeArc Centre for Rare Mitochondrial DiseasesProfessor Patrick Chinnery will lead the LifeArc Centre for Rare Mitochondrial Diseases, a national partnership with the Lily Foundation and Muscular Dystrophy UK, together with key partners at UCL, Newcastle University and three other centres (Oxford, Birmingham and Manchester).
Mitochondrial diseases are genetic disorders affecting 1 in 5,000 people. They often cause progressive damage to the brain, eyes, muscles, heart and liver, leading to severe disability and a shorter life. There is currently have no cure for most conditions, however, new opportunities to treat mitochondrial diseases have been identified in the last five years, meaning that it’s a critical time for research development. The £7.5M centre will establish a national platform that will connect patient groups, knowledge and infrastructure in order to accelerate new treatments getting to clinical trial.
Professor Chinnery said: “The new LifeArc centre unites scientific and clinical strengths from across the UK. For the first time we will form a single team, focussed on developing new treatments for mitochondrial diseases which currently have no cure.”
Adam Harraway has Mitochondrial Disease and says he lives in constant fear of what might go wrong next with his condition. “With rare diseases such as these, it can feel like the questions always outweigh the answers. The news of this investment from LifeArc fills me with hope for the future. To know that there are so many wonderful people and organisations working towards treatments and cures makes me feel seen and heard. It gives a voice to people who often have to suffer in silence, and I'm excited to see how this project can help Mito patients in the future."
LifeArc Centre for Rare Respiratory DiseasesProfessor Stefan Marciniak will co-lead the LifeArc Centre for Rare Respiratory Diseases, a UK wide collaborative centre co-created in partnership with patients and charities. This Centre is a partnership between Universities and NHS Trusts across the UK, co-led by Edinburgh with Nottingham, Dundee, Cambridge, Southampton, University College London and supported by six other centres (Belfast, Cardiff, Leeds, Leicester, Manchester and Royal Brompton).
For the first time ever, it will provide a single ‘go to’ centre that will connect children and adults with rare respiratory disease with clinical experts, researchers, investors and industry leaders across the UK. The £9.4M centre will create a UK-wide biobank of patient samples and models of disease that will allow researchers to advance pioneering therapies and engage with industry and regulatory partners to develop innovative human clinical studies.
Professor Marciniak said: “There are many rare lung diseases, and together those affected constitute a larger underserved group of patients. The National Translational Centre for Rare Respiratory Diseases brings together expertise from across the UK to find effective treatments and train the next generation of rare disease researchers.”
Former BBC News journalist and presenter, Philippa Thomas, has the rare incurable lung disease, Lymphangioleiomyomatosis (LAM). Her condition has stabilised but for many people, the disease can be severely life-limiting. Philippa said: “There is so little research funding for rare respiratory diseases, that getting treatment - let alone an accurate diagnosis - really does feel like a lottery. It is also terrifying being diagnosed with something your GP will never have heard of.”
Globally, there are more than 300 million people living with rare diseases. However, rare disease research can be fragmented. Researchers can lack access to specialist facilities, as well as advice on regulation, trial designs, preclinical regulatory requirements, and translational project management, which are vital in getting new innovations to patients.
Dr Catriona Crombie, Head of Rare Disease at LifeArc, says: “We’re extremely proud to be launching four new LifeArc Translational Centres for Rare Diseases. Each centre has been awarded funding because it holds real promise for delivering change for people living with rare diseases. These centres also have the potential to create a blueprint for accelerating improvements across other disease areas, including common diseases.”
Adapted from a press release from LifeArc
Cambridge researchers will play key roles in two new centres dedicated to developing improved tests, treatments and potentially cures for thousands of people living with rare medical conditions.
The new LifeArc centre unites scientific and clinical strengths from across the UKPatrick ChinneryAlexander_Safonov (Getty)Woman inhaling from a mask nebulizer
The text in this work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Images, including our videos, are Copyright ©University of Cambridge and licensors/contributors as identified. All rights reserved. We make our image and video content available in a number of ways – on our main website under its Terms and conditions, and on a range of channels including social media that permit your use and sharing of our content under their respective Terms.
The IRE1α-XBP1 arm of the unfolded protein response is a host factor activated in SARS-CoV-2 infection
Biochim Biophys Acta Mol Basis Dis. 2024 Apr 20:167193. doi: 10.1016/j.bbadis.2024.167193. Online ahead of print.
ABSTRACT
SARS-CoV-2 infection can cause severe pneumonia, wherein exacerbated inflammation plays a major role. This is reminiscent of the process commonly termed cytokine storm, a condition dependent on a disproportionated production of cytokines. This state involves the activation of the innate immune response by viral patterns and coincides with the biosynthesis of the biomass required for viral replication, which may overwhelm the capacity of the endoplasmic reticulum and drive the unfolded protein response (UPR). The UPR is a signal transduction pathway composed of three branches that is initiated by a set of sensors: inositol-requiring protein 1 (IRE1), protein kinase RNA-like ER kinase (PERK), and activating transcription factor 6 (ATF6). These sensors control adaptive processes, including the transcriptional regulation of proinflammatory cytokines. Based on this background, the role of the UPR in SARS-CoV-2 replication and the ensuing inflammatory response was investigated using in vivo and in vitro models of infection. Mice and Syrian hamsters infected with SARS-CoV-2 showed a sole activation of the Ire1α-Xbp1 arm of the UPR associated with a robust production of proinflammatory cytokines. Human lung epithelial cells showed the dependence of viral replication on the expression of UPR-target proteins branching on the IRE1α-XBP1 arm and to a lower extent on the PERK route. Likewise, activation of the IRE1α-XBP1 branch by Spike (S) proteins from different variants of concern was a uniform finding. These results show that the IRE1α-XBP1 system enhances viral replication and cytokine expression and may represent a potential therapeutic target in SARS-CoV-2 severe pneumonia.
PMID:38648902 | DOI:10.1016/j.bbadis.2024.167193
Recognition of nonself is necessary to activate Drosophila's immune response against an insect parasite
BMC Biol. 2024 Apr 22;22(1):89. doi: 10.1186/s12915-024-01886-1.
ABSTRACT
BACKGROUND: Innate immune responses can be activated by pathogen-associated molecular patterns (PAMPs), danger signals released by damaged tissues, or the absence of self-molecules that inhibit immunity. As PAMPs are typically conserved across broad groups of pathogens but absent from the host, it is unclear whether they allow hosts to recognize parasites that are phylogenetically similar to themselves, such as parasitoid wasps infecting insects.
RESULTS: Parasitoids must penetrate the cuticle of Drosophila larvae to inject their eggs. In line with previous results, we found that the danger signal of wounding triggers the differentiation of specialized immune cells called lamellocytes. However, using oil droplets to mimic infection by a parasitoid wasp egg, we found that this does not activate the melanization response. This aspect of the immune response also requires exposure to parasite molecules. The unidentified factor enhances the transcriptional response in hemocytes and induces a specific response in the fat body.
CONCLUSIONS: We conclude that a combination of danger signals and the recognition of nonself molecules is required to activate Drosophila's immune response against parasitic insects.
PMID:38644510 | PMC:PMC11034056 | DOI:10.1186/s12915-024-01886-1
Risks of releasing imperfect Wolbachia strains for arbovirus control
Lancet Microbe. 2024 Apr 17:S2666-5247(24)00072-7. doi: 10.1016/S2666-5247(24)00072-7. Online ahead of print.
NO ABSTRACT
PMID:38642566 | DOI:10.1016/S2666-5247(24)00072-7
Wed 15 May 13:00: Bradford Hill seminar - Is perfection the enemy of good? Challenges and opportunities for building the evidence-base to inform sexual and reproductive health policy and practice
All are welcome to our next hybrid Bradford Hill Seminar by Prof Cath Mercer of the UCL Institute for Global Health, who will discuss:
‘Is perfection the enemy of good? Challenges and opportunities for building the evidence-base to inform sexual and reproductive health policy and practice’.
This will be a hybrid event
No registration required to attend in person at:
Large Seminar Room, East Forvie Building, Forvie Site, Robinson Way, Cambridge CB2 0SRT .
Registration required to attend online
Please register in Teams in advance at https://rb.gy/4svy5i
About this talk
Poor sexual and reproductive health causes significant morbidity. Last year, nearly 400,000 new sexually transmitted infections were diagnosed in England alone. Additionally, there is increasing awareness of sexual rights, the role of sexual pleasure and wellbeing, and what these mean for a satisfying sex life and our general health and wellbeing.
Yet this critical aspect of our lives is highly sensitive and sometimes stigmatised making sexual behaviour, its drivers and consequences difficult to research. Methods are required that maximise response and minimise bias so that the resulting evidence is of sufficient quality, including for informing policy and practice.
Such methodological rigour is neither cheap nor quick, and since the COVID -19 pandemic shifted expectations around both the timelines for acquiring evidence and the public’s willingness to participate in research, do we need to re-think how we do research in challenging fields such as sexual and reproductive health? Do we need to revise in our definition of what is ‘good enough’?
About Professor Cath Mercer
Cath Mercer is Professor of Sexual Health Science at University College London. A statistician and demographer by training, Cath is internationally recognised as an expert in developing and employing robust methods that advance the scientific study of sexual behaviour, one of the most socially-sensitive disciplines, leading studies that work for – and with – marginalised communities through to the general population, in a variety of settings, employing a range of study designs and research methods.
- Speaker: Professor Cath Mercer, UCL Institute for Global Health
- Wednesday 15 May 2024, 13:00-14:00
- Venue: Large Seminar Room, East Forvie Building, Forvie Site Robinson Way Cambridge CB2 0SR..
- Series: Bradford Hill Seminars; organiser: Paul Browne.
Wed 15 May 13:00: Bradford Hill seminar - Is perfection the enemy of good? Challenges and opportunities for building the evidence-base to inform sexual and reproductive health policy and practice
All are welcome to our next hybrid Bradford Hill Seminar by Prof Cath Mercer of the UCL Institute for Global Health, who will discuss:
‘Is perfection the enemy of good? Challenges and opportunities for building the evidence-base to inform sexual and reproductive health policy and practice’.
This will be a hybrid event
No registration required to attend in person at:
Large Seminar Room, East Forvie Building, Forvie Site, Robinson Way, Cambridge CB2 0SRT .
Registration required to attend online
Please register in Teams in advance at https://rb.gy/4svy5i
About this talk
Poor sexual and reproductive health causes significant morbidity. Last year, nearly 400,000 new sexually transmitted infections were diagnosed in England alone. Additionally, there is increasing awareness of sexual rights, the role of sexual pleasure and wellbeing, and what these mean for a satisfying sex life and our general health and wellbeing.
Yet this critical aspect of our lives is highly sensitive and sometimes stigmatised making sexual behaviour, its drivers and consequences difficult to research. Methods are required that maximise response and minimise bias so that the resulting evidence is of sufficient quality, including for informing policy and practice.
Such methodological rigour is neither cheap nor quick, and since the COVID -19 pandemic shifted expectations around both the timelines for acquiring evidence and the public’s willingness to participate in research, do we need to re-think how we do research in challenging fields such as sexual and reproductive health? Do we need to revise in our definition of what is ‘good enough’?
About Professor Cath Mercer
Cath Mercer is Professor of Sexual Health Science at University College London. A statistician and demographer by training, Cath is internationally recognised as an expert in developing and employing robust methods that advance the scientific study of sexual behaviour, one of the most socially-sensitive disciplines, leading studies that work for – and with – marginalised communities through to the general population, in a variety of settings, employing a range of study designs and research methods.
- Speaker: Professor Cath Mercer, UCL Institute for Global Health
- Wednesday 15 May 2024, 13:00-14:00
- Venue: Large Seminar Room, East Forvie Building, Forvie Site Robinson Way Cambridge CB2 0SR..
- Series: Bradford Hill Seminars; organiser: Paul Browne.
Wed 15 May 13:00: Bradford Hill seminar - Is perfection the enemy of good? Challenges and opportunities for building the evidence-base to inform sexual and reproductive health policy and practice
All are welcome to our next hybrid Bradford Hill Seminar by Prof Cath Mercer of the UCL Institute for Global Health, who will discuss:
‘Is perfection the enemy of good? Challenges and opportunities for building the evidence-base to inform sexual and reproductive health policy and practice’.
This will be a hybrid event
No registration required to attend in person at:
Large Seminar Room, East Forvie Building, Forvie Site, Robinson Way, Cambridge CB2 0SRT .
Registration required to attend online
Please register in Teams in advance at https://rb.gy/4svy5i
About this talk
Poor sexual and reproductive health causes significant morbidity. Last year, nearly 400,000 new sexually transmitted infections were diagnosed in England alone. Additionally, there is increasing awareness of sexual rights, the role of sexual pleasure and wellbeing, and what these mean for a satisfying sex life and our general health and wellbeing.
Yet this critical aspect of our lives is highly sensitive and sometimes stigmatised making sexual behaviour, its drivers and consequences difficult to research. Methods are required that maximise response and minimise bias so that the resulting evidence is of sufficient quality, including for informing policy and practice.
Such methodological rigour is neither cheap nor quick, and since the COVID -19 pandemic shifted expectations around both the timelines for acquiring evidence and the public’s willingness to participate in research, do we need to re-think how we do research in challenging fields such as sexual and reproductive health? Do we need to revise in our definition of what is ‘good enough’?
About Professor Cath Mercer
Cath Mercer is Professor of Sexual Health Science at University College London. A statistician and demographer by training, Cath is internationally recognised as an expert in developing and employing robust methods that advance the scientific study of sexual behaviour, one of the most socially-sensitive disciplines, leading studies that work for – and with – marginalised communities through to the general population, in a variety of settings, employing a range of study designs and research methods.
- Speaker: Professor Cath Mercer, UCL Institute for Global Health
- Wednesday 15 May 2024, 13:00-14:00
- Venue: Large Seminar Room, East Forvie Building, Forvie Site Robinson Way Cambridge CB2 0SR..
- Series: Bradford Hill Seminars; organiser: Paul Browne.
Wed 15 May 13:00: Bradford Hill seminar - Is perfection the enemy of good? Challenges and opportunities for building the evidence-base to inform sexual and reproductive health policy and practice
All are welcome to our next hybrid Bradford Hill Seminar by Prof Cath Mercer of the UCL Institute for Global Health, who will discuss:
‘Is perfection the enemy of good? Challenges and opportunities for building the evidence-base to inform sexual and reproductive health policy and practice’.
This will be a hybrid event
No registration required to attend in person at:
Large Seminar Room, East Forvie Building, Forvie Site, Robinson Way, Cambridge CB2 0SRT .
Registration required to attend online
Please register in Teams in advance at https://rb.gy/4svy5i
About this talk
Poor sexual and reproductive health causes significant morbidity. Last year, nearly 400,000 new sexually transmitted infections were diagnosed in England alone. Additionally, there is increasing awareness of sexual rights, the role of sexual pleasure and wellbeing, and what these mean for a satisfying sex life and our general health and wellbeing.
Yet this critical aspect of our lives is highly sensitive and sometimes stigmatised making sexual behaviour, its drivers and consequences difficult to research. Methods are required that maximise response and minimise bias so that the resulting evidence is of sufficient quality, including for informing policy and practice.
Such methodological rigour is neither cheap nor quick, and since the COVID -19 pandemic shifted expectations around both the timelines for acquiring evidence and the public’s willingness to participate in research, do we need to re-think how we do research in challenging fields such as sexual and reproductive health? Do we need to revise in our definition of what is ‘good enough’?
About Professor Cath Mercer
Cath Mercer is Professor of Sexual Health Science at University College London. A statistician and demographer by training, Cath is internationally recognised as an expert in developing and employing robust methods that advance the scientific study of sexual behaviour, one of the most socially-sensitive disciplines, leading studies that work for – and with – marginalised communities through to the general population, in a variety of settings, employing a range of study designs and research methods.
- Speaker: Professor Cath Mercer, UCL Institute for Global Health
- Wednesday 15 May 2024, 13:00-14:00
- Venue: Large Seminar Room, East Forvie Building, Forvie Site Robinson Way Cambridge CB2 0SR..
- Series: Bradford Hill Seminars; organiser: Paul Browne.
Wed 15 May 13:00: Bradford Hill seminar - Is perfection the enemy of good? Challenges and opportunities for building the evidence-base to inform sexual and reproductive health policy and practice
All are welcome to our next hybrid Bradford Hill Seminar by Prof Cath Mercer of the UCL Institute for Global Health, who will discuss:
‘Is perfection the enemy of good? Challenges and opportunities for building the evidence-base to inform sexual and reproductive health policy and practice’.
This will be a hybrid event
No registration required to attend in person at:
Large Seminar Room, East Forvie Building, Forvie Site, Robinson Way, Cambridge CB2 0SRT .
Registration required to attend online
Please register in advance at https://teams.microsoft.com/registration/W-89URffB0G1Uj26AJ5ZkA,4gqNqQyPO0ORfyzDfqnrLQ,NG69L_hHNkePrbS1cdRxLA,_0aT3zeTQEa1NGghd-e_mw,nYZuQfjZLEW7X-eoyDoKsw,3BREDUKldEemm90D0KOMUQ
About this talk
Poor sexual and reproductive health causes significant morbidity. Last year, nearly 400,000 new sexually transmitted infections were diagnosed in England alone. Additionally, there is increasing awareness of sexual rights, the role of sexual pleasure and wellbeing, and what these mean for a satisfying sex life and our general health and wellbeing.
Yet this critical aspect of our lives is highly sensitive and sometimes stigmatised making sexual behaviour, its drivers and consequences difficult to research. Methods are required that maximise response and minimise bias so that the resulting evidence is of sufficient quality, including for informing policy and practice.
Such methodological rigour is neither cheap nor quick, and since the COVID -19 pandemic shifted expectations around both the timelines for acquiring evidence and the public’s willingness to participate in research, do we need to re-think how we do research in challenging fields such as sexual and reproductive health? Do we need to revise in our definition of what is ‘good enough’?
About Professor Cath Mercer
Cath Mercer is Professor of Sexual Health Science at University College London. A statistician and demographer by training, Cath is internationally recognised as an expert in developing and employing robust methods that advance the scientific study of sexual behaviour, one of the most socially-sensitive disciplines, leading studies that work for – and with – marginalised communities through to the general population, in a variety of settings, employing a range of study designs and research methods.
- Speaker: Professor Cath Mercer, UCL Institute for Global Health
- Wednesday 15 May 2024, 13:00-14:00
- Venue: Large Seminar Room, East Forvie Building, Forvie Site Robinson Way Cambridge CB2 0SR..
- Series: Bradford Hill Seminars; organiser: Paul Browne.
Wed 15 May 13:00: Bradford Hill seminar - Is perfection the enemy of good? Challenges and opportunities for building the evidence-base to inform sexual and reproductive health policy and practice
All are welcome to our next hybrid Bradford Hill Seminar by Prof Cath Mercer of the UCL Institute for Global Health, who will discuss:
‘Is perfection the enemy of good? Challenges and opportunities for building the evidence-base to inform sexual and reproductive health policy and practice’.
This will be a hybrid event
No registration required to attend in person at:
Large Seminar Room, East Forvie Building, Forvie Site, Robinson Way, Cambridge CB2 0SRT .
Registration required to attend online
Please register in advance at https://teams.microsoft.com/registration/W-89URffB0G1Uj26AJ5ZkA,4gqNqQyPO0ORfyzDfqnrLQ,NG69L_hHNkePrbS1cdRxLA,_0aT3zeTQEa1NGghd-e_mw,nYZuQfjZLEW7X-eoyDoKsw,3BREDUKldEemm90D0KOMUQ
About this talk
Poor sexual and reproductive health causes significant morbidity. Last year, nearly 400,000 new sexually transmitted infections were diagnosed in England alone. Additionally, there is increasing awareness of sexual rights, the role of sexual pleasure and wellbeing, and what these mean for a satisfying sex life and our general health and wellbeing.
Yet this critical aspect of our lives is highly sensitive and sometimes stigmatised making sexual behaviour, its drivers and consequences difficult to research. Methods are required that maximise response and minimise bias so that the resulting evidence is of sufficient quality, including for informing policy and practice.
Such methodological rigour is neither cheap nor quick, and since the COVID -19 pandemic shifted expectations around both the timelines for acquiring evidence and the public’s willingness to participate in research, do we need to re-think how we do research in challenging fields such as sexual and reproductive health? Do we need to revise in our definition of what is ‘good enough’?
About Professor Cath Mercer
Cath Mercer is Professor of Sexual Health Science at University College London. A statistician and demographer by training, Cath is internationally recognised as an expert in developing and employing robust methods that advance the scientific study of sexual behaviour, one of the most socially-sensitive disciplines, leading studies that work for – and with – marginalised communities through to the general population, in a variety of settings, employing a range of study designs and research methods.
- Speaker: Professor Cath Mercer, UCL Institute for Global Health
- Wednesday 15 May 2024, 13:00-14:00
- Venue: Large Seminar Room, East Forvie Building, Forvie Site Robinson Way Cambridge CB2 0SR..
- Series: Bradford Hill Seminars; organiser: Paul Browne.
Training AI models to answer ‘what if?’ questions could improve medical treatments
Artificial intelligence techniques can be helpful for multiple medical applications, such as radiology or oncology, where the ability to recognise patterns in large volumes of data is vital. For these types of applications, the AI compares information against learned examples, draws conclusions, and makes extrapolations.
Now, an international team led by researchers from Ludwig-Maximilians-Universität München (LMU) and including researchers from the University of Cambridge, is exploring the potential of a comparatively new branch of AI for diagnostics and therapy.
The researchers found that causal machine learning (ML) can estimate treatment outcomes – and do so better than the machine learning methods generally used to date. Causal machine learning makes it easier for clinicians to personalise treatment strategies, which individually improves the health of patients.
The results, reported in the journal Nature Medicine, suggest how causal machine learning could improve the effectiveness and safety of a variety of medical treatments.
Classical machine learning recognises patterns and discovers correlations. However, the principle of cause and effect remains closed to machines as a rule; they cannot address the question of why. When making therapy decisions for a patient, the ‘why’ is vital to achieve the best outcomes.
“Developing machine learning tools to address why and what if questions is empowering for clinicians, because it can strengthen their decision-making processes,” said senior author Professor Michaela van der Schaar, Director of the Cambridge Centre for AI in Medicine. “But this sort of machine learning is far more complex than assessing personalised risk.”
For example, when attempting to determine therapy decisions for someone at risk of developing diabetes, classical ML would aim to predict how probable it is for a given patient with a range of risk factors to develop the disease. With causal ML, it would be possible to answer how the risk changes if the patient receives an anti-diabetes drug; that is, gauge the effect of a cause. It would also be possible to estimate whether metformin, the commonly-prescribed medication, would be the best treatment, or whether another treatment plan would be better.
To be able to estimate the effect of a hypothetical treatment, the AI models must learn to answer ‘what if?’ questions. “We give the machine rules for recognising the causal structure and correctly formalising the problem,” said Professor Stefan Feuerriegel from LMU, who led the research. “Then the machine has to learn to recognise the effects of interventions and understand, so to speak, how real-life consequences are mirrored in the data that has been fed into the computers.”
Even in situations for which reliable treatment standards do not yet exist or where randomised studies are not possible for ethical reasons because they always contain a placebo group, machines could still gauge potential treatment outcomes from the available patient data and form hypotheses for possible treatment plans, so the researchers hope.
With such real-world data, it should generally be possible to describe the patient cohorts with ever greater precision in the estimates, bringing individualised therapy decisions that much closer. Naturally, there would still be the challenge of ensuring the reliability and robustness of the methods.
“The software we need for causal ML methods in medicine doesn’t exist out of the box,” says Feuerriegel. “Rather, complex modelling of the respective problem is required, involving close collaboration between AI experts and doctors.”
In other fields, such as marketing, explains Feuerriegel, the work with causal ML has already been in the testing phase for some years now. “Our goal is to bring the methods a step closer to practice,” he said. The paper describes the direction in which things could move over the coming years.”
“I have worked in this area for almost 10 years, working relentlessly in our lab with generations of students to crack this problem,” said van der Schaar, who is affiliated with the Departments of Applied Mathematics and Theoretical Physics, Engineering and Medicine. “It’s an extremely challenging area of machine learning, and seeing it come closer to clinical use, where it will empower clinicians and patients alike, is very satisfying.”
Van der Schaar is continuing to work closely with clinicians to validate these tools in diverse clinical settings, including transplantation, cancer and cardiovascular disease.
Reference:
Stefan Feuerriegel et al. ‘Causal machine learning for predicting treatments.’ Nature Medicine (2024). DOI: 10.1038/s41591-024-02902-1
Adapted from an LMU media release.
Machines can learn not only to make predictions, but to handle causal relationships. An international research team shows how this could make medical treatments safer, more efficient, and more personalised.
Yuichiro Chino via Getty ImagesComputer-generated image of human brain
The text in this work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Images, including our videos, are Copyright ©University of Cambridge and licensors/contributors as identified. All rights reserved. We make our image and video content available in a number of ways – on our main website under its Terms and conditions, and on a range of channels including social media that permit your use and sharing of our content under their respective Terms.
Mess is best: disordered structure of battery-like devices improves performance
Researchers led by the University of Cambridge used experimental and computer modelling techniques to study the porous carbon electrodes used in supercapacitors. They found that electrodes with a more disordered chemical structure stored far more energy than electrodes with a highly ordered structure.
Supercapacitors are a key technology for the energy transition and could be useful for certain forms of public transport, as well as for managing intermittent solar and wind energy generation, but their adoption has been limited by poor energy density.
The researchers say their results, reported in the journal Science, represent a breakthrough in the field and could reinvigorate the development of this important net-zero technology.
Like batteries, supercapacitors store energy, but supercapacitors can charge in seconds or a few minutes, while batteries take much longer. Supercapacitors are far more durable than batteries, and can last for millions of charge cycles. However, the low energy density of supercapacitors makes them unsuitable for delivering long-term energy storage or continuous power.
“Supercapacitors are a complementary technology to batteries, rather than a replacement,” said Dr Alex Forse from Cambridge’s Yusuf Hamied Department of Chemistry, who led the research. “Their durability and extremely fast charging capabilities make them useful for a wide range of applications.”
A bus, train or metro powered by supercapacitors, for example, could fully charge in the time it takes to let passengers off and on, providing it with enough power to reach the next stop. This would eliminate the need to install any charging infrastructure along the line. However, before supercapacitors are put into widespread use, their energy storage capacity needs to be improved.
While a battery uses chemical reactions to store and release charge, a supercapacitor relies on the movement of charged molecules between porous carbon electrodes, which have a highly disordered structure. “Think of a sheet of graphene, which has a highly ordered chemical structure,” said Forse. “If you scrunch up that sheet of graphene into a ball, you have a disordered mess, which is sort of like the electrode in a supercapacitor.”
Because of the inherent messiness of the electrodes, it’s been difficult for scientists to study them and determine which parameters are the most important when attempting to improve performance. This lack of clear consensus has led to the field getting a bit stuck.
Many scientists have thought that the size of the tiny holes, or nanopores, in the carbon electrodes was the key to improved energy capacity. However, the Cambridge team analysed a series of commercially available nanoporous carbon electrodes and found there was no link between pore size and storage capacity.
Forse and his colleagues took a new approach and used nuclear magnetic resonance (NMR) spectroscopy – a sort of ‘MRI’ for batteries – to study the electrode materials. They found that the messiness of the materials – long thought to be a hindrance – was the key to their success.
“Using NMR spectroscopy, we found that energy storage capacity correlates with how disordered the materials are – the more disordered materials can store more energy,” said first author Xinyu Liu, a PhD candidate co-supervised by Forse and Professor Dame Clare Grey. “Messiness is hard to measure – it’s only possible thanks to new NMR and simulation techniques, which is why messiness is a characteristic that’s been overlooked in this field.”
When analysing the electrode materials with NMR spectroscopy, a spectrum with different peaks and valleys is produced. The position of the peak indicates how ordered or disordered the carbon is. “It wasn’t our plan to look for this, it was a big surprise,” said Forse. “When we plotted the position of the peak against energy capacity, a striking correlation came through – the most disordered materials had a capacity almost double that of the most ordered materials.”
So why is mess good? Forse says that’s the next thing the team is working on. More disordered carbons store ions more efficiently in their nanopores, and the team hope to use these results to design better supercapacitors. The messiness of the materials is determined at the point they are synthesised.
“We want to look at new ways of making these materials, to see how far messiness can take you in terms of improving energy storage,” said Forse. “It could be a turning point for a field that’s been stuck for a little while. Clare and I started working on this topic over a decade ago, and it’s exciting to see a lot of our previous fundamental work now having a clear application.”
The research was supported in part by the Cambridge Trusts, the European Research Council, and UK Research and Innovation (UKRI).
Reference:
Xinyu Liu et al. ‘Structural disorder determines capacitance in nanoporous carbons.’ Science (2024). DOI: 10.1126/science.adn6242
For more information on energy-related research in Cambridge, please visit the Energy IRC, which brings together Cambridge’s research knowledge and expertise, in collaboration with global partners, to create solutions for a sustainable and resilient energy landscape for generations to come.
The energy density of supercapacitors – battery-like devices that can charge in seconds or a few minutes – can be improved by increasing the ‘messiness’ of their internal structure.
This could be a turning point for a field that’s been stuck for a little while. Alex ForseNathan PittLeft to right: Clare Grey, Xinyu Liu, Alex Forse
The text in this work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Images, including our videos, are Copyright ©University of Cambridge and licensors/contributors as identified. All rights reserved. We make our image and video content available in a number of ways – on our main website under its Terms and conditions, and on a range of channels including social media that permit your use and sharing of our content under their respective Terms.
Tue 04 Jun 12:00: DNA damage response control by RNA and its therapeutic potential
Abstract not available
- Speaker: Fabrizio d'Adda di Fagagna
- Tuesday 04 June 2024, 12:00-13:00
- Venue: Jean Thomas Lecture theatre, Sanger Building, Tennis Court Road.
- Series: Department of Biochemistry - Tea Club Seminars; organiser: reception.
Tue 04 Jun 12:00: DNA damage response control by RNA and its therapeutic potential
Abstract not available
- Speaker: Fabrizio d'Adda di Fagagna
- Tuesday 04 June 2024, 12:00-13:00
- Venue: Jean Thomas Lecture theatre, Sanger Building, Tennis Court Road.
- Series: Department of Biochemistry - Tea Club Seminars; organiser: reception.
Sea stack plots: Replacing bar charts with histograms
Ecol Evol. 2024 Apr 16;14(4):e11237. doi: 10.1002/ece3.11237. eCollection 2024 Apr.
ABSTRACT
Graphs in research articles can increase the comprehension of statistical data but may mislead readers if poorly designed. We propose a new plot type, the sea stack plot, which combines vertical histograms and summary statistics to represent large univariate datasets accurately, usefully, and efficiently. We compare five commonly used plot types (dot and whisker plots, boxplots, density plots, univariate scatter plots, and dot plots) to assess their relative strengths and weaknesses when representing distributions of data commonly observed in biological studies. We find the assessed plot types are either difficult to read at large sample sizes or have the potential to misrepresent certain distributions of data, showing the need for an improved method of data visualisation. We present an analysis of the plot types used in four ecology and conservation journals covering multiple areas of these research fields, finding widespread use of uninformative bar charts and dot and whisker plots (60% of all panels showing univariate data from multiple groups for the purpose of comparison). Some articles presented more informative figures by combining plot types (16% of panels), generally boxplots and a second layer such as a flat density plot, to better display the data. This shows an appetite for more effective plot types within conservation and ecology, which may further increase if accurate and user-friendly plot types were made available. Finally, we describe sea stack plots and explain how they overcome the weaknesses associated with other alternatives to uninformative plots when used for large and/or unevenly distributed data. We provide a tool to create sea stack plots with our R package 'seastackplot', available through GitHub.
PMID:38633526 | PMC:PMC11021675 | DOI:10.1002/ece3.11237
No evidence that a transmissible cancer has shifted from emergence to endemism in Tasmanian devils
R Soc Open Sci. 2024 Apr 17;11(4):231875. doi: 10.1098/rsos.231875. eCollection 2024 Apr.
ABSTRACT
Tasmanian devils are endangered by a transmissible cancer known as Tasmanian devil facial tumour 1 (DFT1). A 2020 study by Patton et al. (Science 370, eabb9772 (doi:10.1126/science.abb9772)) used genome data from DFT1 tumours to produce a dated phylogenetic tree for this transmissible cancer lineage, and thence, using phylodynamics models, to estimate its epidemiological parameters and predict its future trajectory. It concluded that the effective reproduction number for DFT1 had declined to a value of one, and that the disease had shifted from emergence to endemism. We show that the study is based on erroneous mutation calls and flawed methodology, and that its conclusions cannot be substantiated.
PMID:38633353 | PMC:PMC11022658 | DOI:10.1098/rsos.231875
Steven Barrett appointed Regius Professor of Engineering
Professor Steven Barrett has been appointed Regius Professor of Engineering at the University of Cambridge, effective 1 June. He joins the University from the Massachusetts Institute of Technology (MIT), where he is head of the Department of Aeronautics and Astronautics (AeroAstro).
Barrett’s appointment marks his return to Cambridge, where he was an undergraduate at Pembroke College, and received his PhD. He was a Lecturer in the Department of Engineering from 2008 until 2010, when he joined the faculty at MIT.
The Regius Professorships are royal academic titles created by the monarch. The Regius Professorship in Engineering was announced in 2011, in honour of HRH Prince Philip, The Duke of Edinburgh’s 35 years as Chancellor of the University.
“It’s a pleasure to welcome Steven back to Cambridge to take up one of the University’s most prestigious roles,” said Vice-Chancellor Professor Deborah Prentice. “His work on sustainable aviation will build on Cambridge’s existing strengths, and will help us develop the solutions we need to address the threat posed by climate change.”
Barrett’s research focuses on the impact aviation has on the environment. He has developed a number of solutions to mitigate the impact aviation has on air quality, climate, and noise pollution. The overall goal of his research is to help develop technologies that eliminate the environmental impact of aviation. His work on the first-ever plane with no moving propulsion parts was named one of the 10 Breakthroughs of 2018 by Physics World.
“This is an exciting time to work on sustainable aviation, and Cambridge, as well as the UK more generally, is a wonderful platform to advance that,” said Barrett. “Cambridge’s multidisciplinary Department of Engineering, as well as the platform that the Regius Professorship provides, makes this a great opportunity. I’ve learned a lot at MIT, but I’d always hoped to come back to Cambridge at some point.”
Much of Barrett’s research focuses on the elimination of contrails, line-shaped clouds produced by aircraft engine exhaust in cold and humid conditions. Contrails cause half of all aviation-related global warming – more than the entirety of the UK economy. Barrett uses a combination of satellite observation and machine learning techniques to help determine whether avoiding certain regions of airspace could reduce or eliminate contrail formation.
“It will take several years to make this work, but if it does, it could drastically reduce emissions at a very low cost to the consumer,” said Barrett. “We could make the UK the first ‘Blue Skies’ country in the world – the first without any contrails in the sky.”
“Steven’s pioneering work on contrail formation and avoidance is a key element in reducing the environmental impact of aviation, and will strengthen the UK’s position as a world leader in this area,” said Professor Colm Durkan, Head of Cambridge’s Department of Engineering. “Together with Steven’s work on alternative aviation propulsion systems, this will strengthen Cambridge’s vision of helping us all achieve net zero at an accelerated rate.”
In addition to the Professorship in Engineering, there are seven other Regius Professorships at Cambridge: Divinity, Hebrew, Greek, Civil Law and Physic (all founded by Henry VIII in 1540), History (founded by George I in 1724) and Botany (founded in 2009, to mark the University’s 800th anniversary).
An expert on the environmental impacts of aviation, Barrett joins the University of Cambridge from MIT.
MITSteven Barrett
The text in this work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Images, including our videos, are Copyright ©University of Cambridge and licensors/contributors as identified. All rights reserved. We make our image and video content available in a number of ways – on our main website under its Terms and conditions, and on a range of channels including social media that permit your use and sharing of our content under their respective Terms.
Artificial Intelligence beats doctors in accurately assessing eye problems
The clinical knowledge and reasoning skills of GPT-4 are approaching the level of specialist eye doctors, a study led by the University of Cambridge has found.
GPT-4 - a ‘large language model’ - was tested against doctors at different stages in their careers, including unspecialised junior doctors, and trainee and expert eye doctors. Each was presented with a series of 87 patient scenarios involving a specific eye problem, and asked to give a diagnosis or advise on treatment by selecting from four options.
GPT-4 scored significantly better in the test than unspecialised junior doctors, who are comparable to general practitioners in their level of specialist eye knowledge.
GPT-4 gained similar scores to trainee and expert eye doctors - although the top performing doctors scored higher.
The researchers say that large language models aren’t likely to replace healthcare professionals, but have the potential to improve healthcare as part of the clinical workflow.
They say state-of-the-art large language models like GPT-4 could be useful for providing eye-related advice, diagnosis, and management suggestions in well-controlled contexts, like triaging patients, or where access to specialist healthcare professionals is limited.
“We could realistically deploy AI in triaging patients with eye issues to decide which cases are emergencies that need to be seen by a specialist immediately, which can be seen by a GP, and which don’t need treatment,” said Dr Arun Thirunavukarasu, lead author of the study, which he carried out while a student at the University of Cambridge’s School of Clinical Medicine.
He added: “The models could follow clear algorithms already in use, and we’ve found that GPT-4 is as good as expert clinicians at processing eye symptoms and signs to answer more complicated questions.
“With further development, large language models could also advise GPs who are struggling to get prompt advice from eye doctors. People in the UK are waiting longer than ever for eye care.
Large volumes of clinical text are needed to help fine-tune and develop these models, and work is ongoing around the world to facilitate this.
The researchers say that their study is superior to similar, previous studies because they compared the abilities of AI to practicing doctors, rather than to sets of examination results.
“Doctors aren't revising for exams for their whole career. We wanted to see how AI fared when pitted against to the on-the-spot knowledge and abilities of practicing doctors, to provide a fair comparison,” said Thirunavukarasu, who is now an Academic Foundation Doctor at Oxford University Hospitals NHS Foundation Trust.
He added: “We also need to characterise the capabilities and limitations of commercially available models, as patients may already be using them - rather than the internet - for advice.”
The test included questions about a huge range of eye problems, including extreme light sensitivity, decreased vision, lesions, itchy and painful eyes, taken from a textbook used to test trainee eye doctors. This textbook is not freely available on the internet, making it unlikely that its content was included in GPT-4’s training datasets.
The results are published today in the journal PLOS Digital Health.
“Even taking the future use of AI into account, I think doctors will continue to be in charge of patient care. The most important thing is to empower patients to decide whether they want computer systems to be involved or not. That will be an individual decision for each patient to make,” said Thirunavukarasu.
GPT-4 and GPT-3.5 – or ‘Generative Pre-trained Transformers’ - are trained on datasets containing hundreds of billions of words from articles, books, and other internet sources. These are two examples of large language models; others in wide use include Pathways Language Model 2 (PaLM 2) and Large Language Model Meta AI 2 (LLaMA 2).
The study also tested GPT-3.5, PaLM2, and LLaMA with the same set of questions. GPT-4 gave more accurate responses than all of them.
GPT-4 powers the online chatbot ChatGPT to provide bespoke responses to human queries. In recent months, ChatGPT has attracted significant attention in medicine for attaining passing level performance in medical school examinations, and providing more accurate and empathetic messages than human doctors in response to patient queries.
The field of artificially intelligent large language models is moving very rapidly. Since the study was conducted, more advanced models have been released - which may be even closer to the level of expert eye doctors.
Reference: Thirunavukarasu, A.J. et al: ‘Large language models approach expert-level clinical knowledge and reasoning in ophthalmology: A head-to-head cross-sectional study.’ PLOS Digital Health, April 2024. DOI: 10.1371/journal.pdig.0000341
A study has found that the AI model GPT-4 significantly exceeds the ability of non-specialist doctors to assess eye problems and provide advice.
We could realistically deploy AI in triaging patients with eye issues to decide which cases are emergencies.Arun ThirunavukarasuMavocado on Getty
The text in this work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Images, including our videos, are Copyright ©University of Cambridge and licensors/contributors as identified. All rights reserved. We make our image and video content available in a number of ways – on our main website under its Terms and conditions, and on a range of channels including social media that permit your use and sharing of our content under their respective Terms.
Lipoarabinomannan modification as a source of phenotypic heterogeneity in host-adapted <em>Mycobacterium abscessus</em> isolates
Proc Natl Acad Sci U S A. 2024 Apr 23;121(17):e2403206121. doi: 10.1073/pnas.2403206121. Epub 2024 Apr 17.
ABSTRACT
Mycobacterium abscessus is increasingly recognized as the causative agent of chronic pulmonary infections in humans. One of the genes found to be under strong evolutionary pressure during adaptation of M. abscessus to the human lung is embC which encodes an arabinosyltransferase required for the biosynthesis of the cell envelope lipoglycan, lipoarabinomannan (LAM). To assess the impact of patient-derived embC mutations on the physiology and virulence of M. abscessus, mutations were introduced in the isogenic background of M. abscessus ATCC 19977 and the resulting strains probed for phenotypic changes in a variety of in vitro and host cell-based assays relevant to infection. We show that patient-derived mutational variations in EmbC result in an unexpectedly large number of changes in the physiology of M. abscessus, and its interactions with innate immune cells. Not only did the mutants produce previously unknown forms of LAM with a truncated arabinan domain and 3-linked oligomannoside chains, they also displayed significantly altered cording, sliding motility, and biofilm-forming capacities. The mutants further differed from wild-type M. abscessus in their ability to replicate and induce inflammatory responses in human monocyte-derived macrophages and epithelial cells. The fact that different embC mutations were associated with distinct physiologic and pathogenic outcomes indicates that structural alterations in LAM caused by nonsynonymous nucleotide polymorphisms in embC may be a rapid, one-step, way for M. abscessus to generate broad-spectrum diversity beneficial to survival within the heterogeneous and constantly evolving environment of the infected human airway.
PMID:38630725 | DOI:10.1073/pnas.2403206121
Evaluating the impact of genomic epidemiology of methicillin-resistant <em>Staphylococcus aureus</em> (MRSA) on hospital infection prevention and control decisions
Microb Genom. 2024 Apr;10(4). doi: 10.1099/mgen.0.001235.
ABSTRACT
Genomic epidemiology enhances the ability to detect and refute methicillin-resistant Staphylococcus aureus (MRSA) outbreaks in healthcare settings, but its routine introduction requires further evidence of benefits for patients and resource utilization. We performed a 12 month prospective study at Cambridge University Hospitals NHS Foundation Trust in the UK to capture its impact on hospital infection prevention and control (IPC) decisions. MRSA-positive samples were identified via the hospital microbiology laboratory between November 2018 and November 2019. We included samples from in-patients, clinic out-patients, people reviewed in the Emergency Department and healthcare workers screened by Occupational Health. We sequenced the first MRSA isolate from 823 consecutive individuals, defined their pairwise genetic relatedness, and sought epidemiological links in the hospital and community. Genomic analysis of 823 MRSA isolates identified 72 genetic clusters of two or more isolates containing 339/823 (41 %) of the cases. Epidemiological links were identified between two or more cases for 190 (23 %) individuals in 34/72 clusters. Weekly genomic epidemiology updates were shared with the IPC team, culminating in 49 face-to-face meetings and 21 written communications. Seventeen clusters were identified that were consistent with hospital MRSA transmission, discussion of which led to additional IPC actions in 14 of these. Two outbreaks were also identified where transmission had occurred in the community prior to hospital presentation; these were escalated to relevant IPC teams. We identified 38 instances where two or more in-patients shared a ward location on overlapping dates but carried unrelated MRSA isolates (pseudo-outbreaks); research data led to de-escalation of investigations in six of these. Our findings provide further support for the routine use of genomic epidemiology to enhance and target IPC resources.
PMID:38630616 | DOI:10.1099/mgen.0.001235