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Study aims to improve recovery after cancer treatment in older people

Researchers are studying recovery after bowel cancer treatment in older people, as the REBOUND study looks at ageing changes linked to surgery and care.
The study, Resilience Breakthroughs in Older people Undergoing cancer proceDures, is examining how key “hallmarks of ageing” are affected following bowel cancer treatment in people aged 65 and over.
These are the biological processes that naturally occur as we get older.
The chief investigator and principal investigator of the study, professor Thomas Jackson is professor in geriatric medicine at the University of Birmingham and consultant in geriatric medicine and general internal medicine at University Hospitals Birmingham (UHB).
He said: “This is really important work that couldn’t be done without the support of patients agreeing to be in the study.
“We want to understand how the biology of ageing changes when older people have significant events, such as major surgery, and why some people recover well, and others don’t.
“With this understanding, we can identify ways of improving recovery in everyone and maximising the benefits of cancer treatment.”
Researchers at USB, in collaboration with King’s College London (KCL), are leading the study to understand the factors that influence how well older people recover from cancer treatment and to find ways to keep the body strong.
While age is a known risk factor for developing cancer, treatments such as chemotherapy, immunotherapy (which helps the immune system attack cancer), surgery and radiation therapy can trigger processes in the body that resemble ageing.
By understanding how the body responds to cancer treatment, researchers aim to develop new interventions that could prevent or reduce ageing-related changes and improve the number of years spent in good health. The ultimate goal is to help older people with cancer remain active and continue doing the things that matter most to them.
The study involves analysing DNA for age-related changes, examining gut bacteria from stool samples and assessing changes in blood and fat cells.
Samples will be collected at multiple time points before, during and after surgery.
These biological findings will be compared with tests of memory, thinking, strength and muscle function, alongside information from medical records.
The study aims to recruit 172 participants aged 50 years and older who are scheduled to undergo bowel cancer surgery at UHB, Guy’s and St Thomas’ NHS Foundation Trust and King’s College Hospital NHS Foundation Trust.
The study opened to recruitment in autumn 2024, and to date, 58 patients have been enrolled.
The project is a collaborative effort bringing together clinicians specialising in the care of older people, surgeons and scientists with expertise in ageing and complex data analysis. It is supported by the Dynamic Resilience programme, funded by Wellcome Leap and the Temasek Trust.
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AI can predict Alzheimer’s with almost 93% accuracy, researchers say

Alzheimer’s AI can predict the disease with nearly 93 per cent accuracy using more than 800 brain scans, researchers say.
The system identified anatomical changes in the brain linked to the onset of the most common form of dementia, a condition that gradually damages memory and thinking.
The findings build on years of research suggesting AI could help spot early Alzheimer’s risk, predict disease and identify patients whose condition has not yet been diagnosed.
Benjamin Nephew, an assistant research professor at the Worcester Polytechnic Institute in Massachusetts, said: “Early diagnosis of Alzheimer’s disease can be difficult because symptoms can be mistaken for normal ageing.
“We found that machine-learning technologies, however, can analyse large amounts of data from scans to identify subtle changes and accurately predict Alzheimer’s disease and related cognitive states.”
The study used MRI scans, a type of detailed brain imaging, from 344 people aged 69 to 84.
The dataset included 281 scans showing normal mental function, 332 with mild cognitive impairment, an early stage of memory and thinking decline, and 202 with Alzheimer’s.
The scans covered 95 of the brain’s nearly 200 distinct regions and used an AI algorithm to predict patients’ health.
Being able to use AI to help diagnose Alzheimer’s earlier could give patients and doctors crucial time to prepare and potentially slow the progression of the disease.
The analysis showed that one of the top predictive factors was brain volume loss, or shrinkage, in the hippocampus, which helps form memories, the amygdala, which processes fear, and the entorhinal cortex, which helps provide a sense of time.
This pattern held across age and sex, with both men and women aged 69 to 76 showing volume loss in the right part of the hippocampus, suggesting it may be an important area for early diagnosis, the researchers noted.
However, the research also found that the way brain regions shrink differs by sex.
In females, volume loss occurred in the brain’s left middle temporal cortex, which is involved in language and visual perception. In males, it was mainly seen in the right entorhinal cortex
The researchers believe this could be linked to changes in sex hormones, including the loss of oestrogen in women and testosterone in men.
These conclusions could help improve methods of diagnosis and treatment going forward, Nephew said.
More than 7.2m Americans are living with Alzheimer’s, according to the Alzheimer’s Association.
More research is being done to reveal other impacting factors.
Nephew said: “The critical challenge in this research is to build a generalisable machine-learning model that captures the difference between healthy brains and brains from people with mild cognitive impairment or Alzheimer’s disease.”
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