��Ī - ��Ī and Peterborough NHS Foundation Trust

Dementia patients and their carers to be asked about direction of drug research

cjb250 — Wed, 19 Mar 2025 07:00:07 +0000

Today sees the launch of the POrtal for Patient and Public Engagement in Dementia Research (POPPED) website, where anyone can give their feedback on dementia research projects.

Dementia affects 50 million people worldwide and 1 million people in the UK. Current treatments are limited, but research has led to some significant recent advances. For example, the first drugs which slow down the disease are now licensed in the UK and potential dementia blood tests are being trialled.

Scientists are also turning to existing drugs to see if they may be repurposed to treat dementia. As the safety profile of these drugs is already known, the move to clinical trials can be accelerated significantly. Researchers want to ask members of the public which drugs they would like to see prioritised for these clinical trials.

Dr Ben Underwood, from the Department of Psychiatry at the ��Ī and ��Īshire and Peterborough NHS Foundation Trust, said: “One thing that always improves research into medical conditions is the involvement of people with experience of them – in many respects, you are the experts, rather than us.

“As dementia is common, almost everyone has some experience of it, either through family, friends, work or meeting people with dementia in general life. It’s a problem across society and we want a wide range of opinions for the best way to tackle it.”

Dr Underwood has teamed up with Linda Pointon, a Programme Manager at the Department of Psychiatry, to create a website where everyone can give their feedback on dementia research projects. Linda herself has experience of caring for her mother-in-law, who had frontotemporal dementia and passed away in 2020.

Linda said: “We’re launching our website because we want as many people as possible to share their views and help us guide the direction of our research. It’s a great opportunity for all of us who have been affected by dementia, either directly or caring for a friend or relative, to help researchers understand what aspects of these potential treatments are important and meaningful, both in terms of benefits and side-effects.”

The information collected by the POPPED team will be used to help inform AD-SMART, a trial to be led by Imperial College London, which will test several existing drugs alongside a placebo to quickly determine if any can slow early Alzheimer’s progression.

Dr Underwood added: “Instead of asking a few people what might be helpful, our website gives us the opportunity to ask thousands of people. The more people who use it, the more powerful it will be, so I’d encourage everyone to visit the site and tell us what they think. We can use it to work together to beat dementia, a condition whose effects I see in my clinic every day.”

��Ī researchers are seeking the views of people with lived experience of dementia – patients and their friends and families – on which existing drugs should be repurposed for clinical trials to see whether they can slow or halt the progress of dementia.

One thing that always improves research into medical conditions is the involvement of people with experience of them – in many ways, they are the experts, not us

Ben Underwood

Toa55 (Getty Images)

Elderly woman putting pills into pill box for the week - stock photo

The text in this work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Images, including our videos, are Copyright ©��Ī 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.

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Collaboration Award 2024

zs332 — Mon, 03 Feb 2025 10:55:33 +0000

The 2024 Collaboration Award winner is Representing psychosis in video games: Communicating clinical science and tackling stigma, a project led by Prof Paul Fletcher Department of Psychiatry, School of Clinical Medicine, Clare College.

The ��Ī Awards 2024 for Research Impact and Engagement

zs332 — Mon, 03 Feb 2025 10:27:01 +0000

Meet the winner of the ��Ī Awards 2024 for Research Impact and Engagement and learn more about their projects.

Antibiotics, vaccinations and anti-inflammatory medication linked to reduced risk of dementia

cjb250 — Tue, 21 Jan 2025 12:00:03 +0000

The study, led by researchers from the universities of ��Ī and Exeter, identified several drugs already licensed and in use that have the potential to be repurposed to treat dementia.

Dementia is a leading cause of death in the UK and can lead to profound distress in the individual and among those caring for them. It has been estimated to have a worldwide economic cost in excess of US$1 trillion dollars.

Despite intensive efforts, progress in identifying drugs that can slow or even prevent dementia has been disappointing. Until recently, dementia drugs were effective only for symptoms and have a modest effect. Recently, lecanemab and donanemab have been shown to reduce the build-up in the brain of amyloid plaques – a key characteristic of Alzheimer’s disease – and to slow down progression of the disease, but the National Institute for Health and Care Excellence (NICE) concluded that the benefits were insufficient to justify approval for use within the NHS.

Scientists are increasingly turning to existing drugs to see if they may be repurposed to treat dementia. As the safety profile of these drugs is already known, the move to clinical trials can be accelerated significantly.

Dr Ben Underwood, from the Department of Psychiatry at the ��Ī and ��Īshire and Peterborough NHS Foundation Trust, said: “We urgently need new treatments to slow the progress of dementia, if not to prevent it. If we can find drugs that are already licensed for other conditions, then we can get them into trials and – crucially – may be able to make them available to patients much, much faster than we could do for an entirely new drug. The fact they are already available is likely to reduce cost and therefore make them more likely to be approved for use in the NHS.”

In a study published today in Alzheimer’s and Dementia: Translational Research & Clinical Interventions, Dr Underwood, together with Dr Ilianna Lourida from the University of Exeter, led a systematic review of existing scientific literature to look for evidence of prescription drugs that altered the risk of dementia. Systematic reviews allow researchers to pool several studies where evidence may be weak, or even contradictory, to arrive at more robust conclusions.

In total, the team examined 14 studies that used large clinical datasets and medical records, capturing data from more than 130 million individuals and 1 million dementia cases. Although they found a lack of consistency between studies in identifying individual drugs that affect the risk of dementia, they identified several drug classes associated with altered risk.

One unexpected finding was an association between antibiotics, antivirals and vaccines, and a reduced risk of dementia. This finding supports the hypothesis that common dementias may be triggered by viral or bacterial infections, and supports recent interest in vaccines, such as the BCG vaccine for tuberculosis, and decreased risk of dementia.

Anti-inflammatory drugs such as ibuprofen were also found to be associated with reduced risk. Inflammation is increasingly being seen to be a significant contributor to a wide range of diseases, and its role in dementia is supported by the fact that some genes that increase the risk of dementia are part of inflammatory pathways.

The team found conflicting evidence for several classes of drugs, with some blood pressure medications and anti-depressants and, to a lesser extent, diabetes medication associated with a decreased risk of dementia and others associated with increased risk.

Dr Ilianna Lourida from the National Institute for Health and Care Research Applied Research Collaboration South West Peninsula (PenARC), University of Exeter, said: “Because a particular drug is associated with an altered risk of dementia, it doesn’t necessarily mean that it causes or indeed helps in dementia. We know that diabetes increases your risk of dementia, for example, so anyone on medication to manage their glucose levels would naturally also be at a higher risk of dementia – but that doesn’t mean the drug increases your risk.

“It’s important to remember that all drugs have benefits and risks. You should never change your medicine without discussing this first with your doctor, and you should speak to them if you have any concerns.”

The conflicting evidence may also reflect differences in how particular studies were conducted and how data was collected, as well as the fact that different medications even within the same class often target different biological mechanisms.

The UK government is supporting the development of an Alzheimer’s trial platform to evaluate drugs rapidly and efficiently, including repurposed drugs currently used for other conditions.

“Pooling these massive health data sets provides one source of evidence which we can use to help us focus on which drugs we should try first,” said Dr Underwood. “We’re hopeful this will mean we can find some much-needed new treatments for dementia and speed up the process of getting them to patients.”

Reference
Underwood, BU & Lourida, I et al. Data-driven discovery of associations between prescribed drugs and dementia risk: A systematic review. Alz & Dem; 21 Jan 2025; DOI: 10.1002/trc2.70037

Antibiotics, antivirals, vaccinations and anti-inflammatory medication are associated with reduced risk of dementia, according to new research that looked at health data from over 130 million individuals.

We urgently need new treatments to slow the progress of dementia, if not to prevent it. If we can find drugs that are already licensed for other conditions, then we can get them into trials much faster than we could do for an entirely new drug

Ben Underwood

Andrzej Rostek (Getty Images)

Elderly Woman's Hands and Orange Pills

Yes

Artificial intelligence outperforms clinical tests at predicting progress of Alzheimer’s disease

cjb250 — Fri, 12 Jul 2024 22:30:52 +0000

The team say this new approach could reduce the need for invasive and costly diagnostic tests while improving treatment outcomes early when interventions such as lifestyle changes or new medicines may have a chance to work best.

Dementia poses a significant global healthcare challenge, affecting over 55 million people worldwide at an estimated annual cost of $820 billion. The number of cases is expected to almost treble over the next 50 years.

The main cause of dementia is Alzheimer’s disease, which accounts for 60-80% of cases. Early detection is crucial as this is when treatments are likely to be most effective, yet early dementia diagnosis and prognosis may not be accurate without the use of invasive or expensive tests such as positron emission tomography (PET) scans or lumbar puncture, which are not available in all memory clinics. As a result, up to a third of patients may be misdiagnosed and others diagnosed too late for treatment to be effective.

A team led by scientists from the Department of Psychology at the ��Ī has developed a machine learning model able to predict whether and how fast an individual with mild memory and thinking problems will progress to developing Alzheimer’s disease. In research published today in eClinical Medicine, they show that it is more accurate than current clinical diagnostic tools.

To build their model, the researchers used routinely-collected, non-invasive, and low-cost patient data – cognitive tests and structural MRI scans showing grey matter atrophy – from over 400 individuals who were part of a research cohort in the USA.

They then tested the model using real-world patient data from a further 600 participants from the US cohort and – importantly – longitudinal data from 900 people from memory clinics in the UK and Singapore.

The algorithm was able to distinguish between people with stable mild cognitive impairment and those who progressed to Alzheimer’s disease within a three-year period. It was able to correctly identify individuals who went on to develop Alzheimer’s in 82% of cases and correctly identify those who didn’t in 81% of cases from cognitive tests and an MRI scan alone.

The algorithm was around three times more accurate at predicting the progression to Alzheimer’s than the current standard of care; that is, standard clinical markers (such as grey matter atrophy or cognitive scores) or clinical diagnosis. This shows that the model could significantly reduce misdiagnosis.

The model also allowed the researchers to stratify people with Alzheimer’s disease using data from each person’s first visit at the memory clinic into three groups: those whose symptoms would remain stable (around 50% of participants), those who would progress to Alzheimer’s slowly (around 35%) and those who would progress more rapidly (the remaining 15%). These predictions were validated when looking at follow-up data over 6 years. This is important as it could help identify those people at an early enough stage that they may benefit from new treatments, while also identifying those people who need close monitoring as their condition is likely to deteriorate rapidly.

Importantly, those 50% of people who have symptoms such as memory loss but remain stable, would be better directed to a different clinical pathway as their symptoms may be due to other causes rather than dementia, such as anxiety or depression.

Senior author Professor Zoe Kourtzi from the Department of Psychology at the ��Ī said: “We’ve created a tool which, despite using only data from cognitive tests and MRI scans, is much more sensitive than current approaches at predicting whether someone will progress from mild symptoms to Alzheimer’s – and if so, whether this progress will be fast or slow.

“This has the potential to significantly improve patient wellbeing, showing us which people need closest care, while removing the anxiety for those patients we predict will remain stable. At a time of intense pressure on healthcare resources, this will also help remove the need for unnecessary invasive and costly diagnostic tests.”

While the researchers tested the algorithm on data from a research cohort, it was validated using independent data that included almost 900 individuals who attended memory clinics in the UK and Singapore. In the UK, patients were recruited through the Quantiative MRI in NHS Memory Clinics Study (QMIN-MC) led by study co-author Dr Timothy Rittman at ��Ī University Hospitals NHS Trust and ��Īshire and Peterborough NHS Foundation Trusts (CPFT).

The researchers say this shows it should be applicable in a real-world patient, clinical setting.

Dr Ben Underwood, Honorary Consultant Psychiatrist at CPFT and assistant professor at the Department of Psychiatry, ��Ī, said: “Memory problems are common as we get older. In clinic I see how uncertainty about whether these might be the first signs of dementia can cause a lot of worry for people and their families, as well as being frustrating for doctors who would much prefer to give definitive answers. The fact that we might be able to reduce this uncertainty with information we already have is exciting and is likely to become even more important as new treatments emerge.”

Professor Kourtzi said: “AI models are only as good as the data they are trained on. To make sure ours has the potential to be adopted in a healthcare setting, we trained and tested it on routinely-collected data not just from research cohorts, but from patients in actual memory clinics. This shows it will be generalisable to a real-world setting.”

The team now hope to extend their model to other forms of dementia, such as vascular dementia and frontotemporal dementia, and using different types of data, such as markers from blood tests.

Professor Kourtzi added: “If we’re going to tackle the growing health challenge presented by dementia, we will need better tools for identifying and intervening at the earliest possible stage. Our vision is to scale up our AI tool to help clinicians assign the right person at the right time to the right diagnostic and treatment pathway. Our tool can help match the right patients to clinical trials, accelerating new drug discovery for disease modifying treatments.”

This work was in collaboration with a cross-disciplinary team including Professor Peter Tino at the University of Birmingham and Professor Christopher Chen at the National University of Singapore. It was funded by Wellcome, the Royal Society, Alzheimer’s Research UK, the Alzheimer’s Drug Discovery Foundation Diagnostics Accelerator, the Alan Turing Institute, and the National Institute for Health and Care Research ��Ī Biomedical Research Centre.

Reference
Lee, LY & Vaghari, D et al. Robust and interpretable AI-guided marker for early dementia prediction in real-world clinical settings. eClinMed; 12 July 2024; DOI: 10.1016/j.eclinm.2024.102725

��Ī scientists have developed an artificially-intelligent tool capable of predicting in four cases out of five whether people with early signs of dementia will remain stable or develop Alzheimer’s disease.

We’ve created a tool which is much more sensitive than current approaches at predicting whether someone will progress from mild symptoms to Alzheimer’s

Zoe Kourtzi

Yuichiro Chino (Getty Images)

Brain on molecular structure, circuitry, and programming code background

Yes

Long COVID linked to persistently high levels of inflammatory protein: a potential biomarker and target for treatments

ta385 — Wed, 21 Feb 2024 18:45:00 +0000

A ��Ī-led study identifies the protein interferon gamma (IFN-γ) as a potential biomarker for Long COVID fatigue and highlights an immunological mechanism underlying the disease, which could pave the way for the development of much needed therapies, and provide a head start in the event of a future coronavirus pandemic.

The study, published today in Science Advances, followed a group of patients with Long COVID fatigue for over 2.5 years, to understand why some recovered and others did not.

Long COVID continues to affect millions of people globally and is placing a major burden on health services. An estimated 1.9 million people in the UK alone (2.9% of the population) were experiencing self-reported Long COVID as of March 2023, according to the ONS. Fatigue remains by far the most common and debilitating symptom and patients are still waiting for an effective treatment.

The study shows that initial infection with SARS-CoV-2 triggers production of the antiviral protein IFN-γ, which is a normal reaction from the immune system. For most people, when their infection clears, COVID-19 symptoms cease and production of this protein stops, but the researchers found that high levels of IFN-γ persisted in some Long COVID patients for up to 31 months.

“We have found a potential mechanism underlying Long COVID which could represent a biomarker – that is, a tell-tale signature of the condition. We hope that this could help to pave the way to develop therapies and give some patients a firm diagnosis,” said co-author, Dr Benjamin Krishna, from the ��Ī Institute of Therapeutic Immunology & Infectious Disease (CITIID).

The research began in 2020 when Dr Nyarie Sithole (Hughes Hall) set up a Long COVID clinic in ��Ī’s Addenbrooke’s Hospital, where he started collecting blood samples from patients and set about studying their immunology. Sithole soon enlisted the support of Dr Benjamin Krishna and Dr Mark Wills from the ��Ī’s Department of Medicine.

“When the clinic started, a lot of people didn't even believe Long COVID was real,” Dr Sithole said. “We are indebted to all the patients who volunteered for this study, without whose support and participation we would obviously not have accomplished this study”.

The team studied 111 COVID-confirmed patients admitted to Addenbrooke’s Hospital CUH, Royal Papworth Hospital and ��Ī and Peterborough NHS Foundation Trusts at 28 days, 90 days and 180 days following symptom onset. Between August 2020 and July 2021, they recruited 55 Long COVID patients – all experiencing severe symptoms at least 5 months after acute COVID-19 – attending the Long COVID clinic at Addenbrooke’s.

The researchers analysed blood samples for signs of cytokines, small proteins crucial to the functioning of immune system cells and blood cells. They found that the white blood cells of individuals infected with SARS-CoV-2 produced IFN-γ, a pro inflammatory molecule, and that this persisted in Long COVID patients.

Dr Krishna said: “Interferon gamma can be used to treat viral infections such as hepatitis C but it causes symptoms including fatigue, fever, headache, aching muscles and depression. These symptoms are all too familiar to Long COVID patients. For us, that was another smoking gun.”

By conducting ‘cell depletion assays’, the team managed to identify the precise cell types responsible for producing IFN-γ. They pinpointed immune cells known as CD8+ T cells but found that they required contact with another immune cell type: CD14+ monocytes.

Previous studies have identified IFN-γ signatures using different approaches and cohorts, but this study’s focus on fatigue revealed a much stronger influence. Also, while previous studies have noticed IFN-y levels rising, they have not followed patients long enough to observe when they might drop back down.

The ��Ī team followed its Long COVID cohort for up to 31 months post-infection. During this follow up period, over 60% of patients experienced resolution of some, if not all, of their symptoms which coincided with a drop in IFN-γ.

Vaccination helping Long COVID patients

The team measured IFN-γ release in Long COVID patients before and after vaccination and found a significant decrease in IFN-γ post vaccination in patients whose symptoms resolved.

“If SARS-CoV-2 continues to persist in people with Long COVID, triggering an IFN-γ response, then vaccination may be helping to clear this. But we still need to find effective therapies,” Dr Krishna said.

“The number of people with Long COVID is gradually falling, and vaccination seems to be playing a significant role in that. But new cases are still cropping up, and then there is the big question of what happens when the next coronavirus pandemic comes along. We could face another wave of Long COVID. Understanding what causes Long COVID now could give us a crucial head start.”

Microclotting

Some well-publicised previous studies have proposed microclotting as a principle cause of Long COVID. While not ruling out a role of some kind, these new findings suggest that microclotting cannot be the only or the most significant cause.

Classifying Long COVID

This study argues that the presence of IFN-γ could be used to classify Long COVID into subtypes which could be used to personalise treatment.

“It’s unlikely that all the different Long COVID symptoms are caused by the same thing. We need to differentiate between people and tailor treatments. Some patients are slowly recovering and there are those who are stuck in a cycle of fatigue for years on end. We need to know why,” Dr Krishna said.

Reference

B A Krishna et al., ‘Spontaneous, persistent, T-cell dependent IFN-γ release in patients who progress to long COVID’, Science Advances (2024). DOI: 10.1126/sciadv.adi9379

SARS-CoV-2 triggers the production of the antiviral protein IFN-γ, which is associated with fatigue, muscle ache and depression. New research shows that in Long COVID patients, IFN-y production persists until symptoms improve, highlighting a potential biomarker and a target for therapies.

We hope that this could help to pave the way to develop therapies and give some patients a firm diagnosis

Benjamin Krishna

Annie Spratt via Unsplash

Woman sitting on sofa in the dark, placing a hand to her forehead

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Autistic individuals have increased risk of chronic physical health conditions across the whole body

Anonymous — Fri, 29 Sep 2023 12:38:16 +0000

Previous studies have shown that autistic people are dying far younger than others and that they are more likely to experience a range of physical health conditions. Until now, it was believed that autistic people were more likely to have specific conditions, such as gastrointestinal pain, sleep problems, and epilepsy/seizure disorders.

The new study is different in that it investigated a much wider range of health risks than has been done before and shows that autistic people experience a much broader range of health vulnerabilities than was previously thought.

Specifically, autistic people are more likely to have physical health conditions across all organ systems, including the brain (such as migraine), the gastrointestinal system (for example coeliac disease), and the endocrine system (for example endometriosis), compared to non-autistic people.

Dr Elizabeth Weir, a Research Associate at the Autism Research Centre in ��Ī, who led the team, said: “This study emphasizes the increased health vulnerability of autistic people both in the types and number of conditions they may have. We now need to understand the causes of these increased risks, which are likely multifactorial in nature.”

This is the first study to show that autistic people are more likely than non-autistic people to experience ‘physical health multimorbidity’, meaning that they have at least two or more physical health conditions. These include co-occurring fibromyalgia (which causes chronic pain throughout the body) and polycystic ovarian syndrome (which causes irregular menstrual cycles, infertility, excess hair growth, and acne in women) across different organ systems.

The study was conducted by a team at the ARC and used an anonymized, self-report survey to compare the experiences of 1,129 autistic people with 1,176 non-autistic people aged 16-90 years. The participants were international, although 67% of participants were from the UK.

The survey assessed risk of 60 physical health conditions across nine different organ systems (gastrointestinal, endocrine, rheumatological, neurological, ocular, renal/hepatic, otolaryngological, haematological, and dermatological). The analysis took into account other factors such as age, sex assigned at birth, country of residence, ethnicity, education-level, alcohol use, smoking, body mass index, and family medical history.

The team found that autistic people were more likely to have diagnosed medical conditions across all nine organ systems tested, compared to non-autistic people. Regarding specific conditions, autistic people had higher rates of 33 specific conditions compared to non-autistic peers. These included coeliac disease, gallbladder disease, endometriosis, syncope (fainting or passing out), vertigo, urinary incontinence, eczema, and iron deficiency anaemia.

Dr John Ward, a visiting research scientist at the ARC in ��Ī, who conducted the analysis, said: “This research adds to the body of evidence that the healthcare needs of autistic people are greater than those of non-autistic people. More research is required, particularly surrounding the early identification, and monitoring of chronic conditions.”

This is also the first epidemiological study to show that Ehlers-Danlos Syndrome (EDS) – a group of disorders that affects connective tissues and which cause symptoms such as joint hypermobility, loose joints that dislocate easily, joint pain and clicking joints, skin that bruises easily, extreme tiredness, digestive problems, dizziness, stretchy skin, wounds that are slow to heal, organ prolapse, and hernias – may be more common among autistic women than non-autistic women.

The new research also replicates previous findings to show that autistic people have higher rates of all central sensitivity syndromes, which are a varied group of conditions that are related to dysregulation of the central nervous system, compared to non-autistic people. Central sensitivity syndromes include irritable bowel syndrome (IBS), temporomandibular joint syndrome (TMJ), migraine, tinnitus, myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), and fibromyalgia.

The new study also investigated risks of physical health multimorbidity with a novel application of ‘network analysis’, a technique used to understand relationships between different parts of a system. This analysis method is regularly used in neuroscience to understand how different regions of the brain interact with each other. In this study, the analysis assessed how often conditions from different organ systems occurred together in the same person. In addition to highlighting complex health needs, this analysis established for the first time that the combinations of medical conditions that frequently co-occur may be different between autistic and non-autistic adults.

These results are preliminary evidence that healthcare providers such as GPs or family physicians need to be monitoring the health care needs of autistic people much more closely.

Dr Carrie Allison, Director of Strategy at the ARC and a member of the team, added: “These findings highlight the acute need to adapt the healthcare system to better meet the needs of autistic people. These results must be confirmed in larger, population-based samples.”

Professor Sir Simon Baron-Cohen, Director of the ARC and another member of the team, said: “We are aware of the risks of mental health conditions in autistic people, but this new research identifies their risks of physical health conditions too. We need to urgently re-evaluate current health care systems to improve support for autistic people.”

Funding for this project was provided by the Autism Centre of Excellence at ��Ī, the Rosetrees Trust, the ��Ī and Peterborough NHS Foundation Trust, the Corbin Charitable Trust, the Queen Anne’s Gate Foundation, the MRC, the Wellcome Trust and the Innovative Medicines Initiative.

Reference

Ward, J & Weir, E, Allison, C, Baron-Cohen, S. Increased rates of chronic physical health conditions across all organ systems in autistic adolescents and adults. Molecular Autism (2023).

Autistic people have higher rates of chronic physical health conditions across the whole body and are more likely to have complex health needs, according to a study led by researchers at the ��Ī. Their findings, published in the journal Molecular Autism, have important implications for the clinical care of autistic people.

This study emphasizes the increased health vulnerability of autistic people both in the types and number of conditions they may have

Elizabeth Weir

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Two autistic friends sitting outside using stim toys and laughing at their phones

The text in this work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Images, including our videos, are Copyright ©��Ī and licensors/contributors as identified. All rights reserved. We make our image and video content available in a number of ways – as here, 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.

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A very healthy relationship: the University and the NHS

cjb250 — Mon, 03 Jul 2023 15:40:21 +0000

As the NHS celebrates its 75th anniversary, we look at how the close relationship between the University and the hospitals on its doorstep is driving major improvements in how we care for patients.

�������������Ī - �������������Ī and Peterborough NHS Foundation Trust

Dementia patients and their carers to be asked about direction of drug research

Collaboration Award 2024

The �������������Ī Awards 2024 for Research Impact and Engagement

Antibiotics, vaccinations and anti-inflammatory medication linked to reduced risk of dementia

Artificial intelligence outperforms clinical tests at predicting progress of Alzheimer’s disease

Long COVID linked to persistently high levels of inflammatory protein: a potential biomarker and target for treatments

Vaccination helping Long COVID patients

Microclotting

Classifying Long COVID

Reference

Autistic individuals have increased risk of chronic physical health conditions across the whole body

Reference

A very healthy relationship: the University and the NHS

��Ī - ��Ī and Peterborough NHS Foundation Trust

The ��Ī Awards 2024 for Research Impact and Engagement