Connect with us

Alzheimer's Research

AI Accurately Diagnoses Celiac Disease, Reducing Pressure on Pathologists

A machine learning algorithm was able to correctly identify in 97 cases out of 100 whether or not an individual had Celiac disease based on their biopsy, new research has shown. The AI tool, which has been trained on almost 3,400 scanned biopsies from four hospitals, could speed up diagnosis of the condition and take pressure off stretched healthcare resources, as well as improving diagnosis in developing nations, where shortages of pathologists are severe.

Avatar photo

Published

on

The article reports on groundbreaking research conducted by Cambridge scientists that has successfully developed a machine learning algorithm capable of accurately diagnosing Celiac disease in 97 out of 100 cases based on biopsy samples. This study sheds light on the potential of AI to speed up diagnoses, alleviate pressure on pathologists, and improve diagnostic accuracy in developing nations.

To diagnose Celiac disease, pathologists traditionally rely on a biopsy of the duodenum (part of the small intestine), analyzing the sample under a microscope or on a computer using the Marsh-Oberhuber scale. However, this process can be subjective, leading to discrepancies among pathologists.

The researchers from Cambridge developed an AI algorithm trained on over 4,000 images obtained from five different hospitals using various scanners. This comprehensive training dataset enabled the model to accurately classify biopsy image data and reach conclusions comparable to those of experienced pathologists.

In a separate study, four pathologists were asked to review 30 slides and found that they agreed with the AI model as often as with each other. The AI algorithm demonstrated impressive sensitivity (95%) and specificity (98%), indicating its potential for accurate diagnosis.

Dr Florian Jaeckle emphasized that this is the first time an AI has been shown to diagnose Celiac disease with the same accuracy as an experienced pathologist, and highlighted the importance of “explainability” – being able to understand and explain how AI reaches its diagnosis.

The researchers have established a spinout company, Lyzeum Ltd, to commercialize the algorithm, and their collaboration with patient groups has shown receptiveness to technology like this being used. This study offers promising insights into the potential of AI-powered diagnostics to improve healthcare outcomes and reduce pressure on pathologists in the NHS and globally.

Alzheimer's

Early Menopause Linked to Cognitive Decline: A Study on Women’s Risk Factors

Why does dementia affect more women than men? To help solve this mystery, researchers uncovered a new risk factor: age of menopause onset.

Avatar photo

Published

on

The article “Early Menopause Linked to Cognitive Decline: A Study on Women’s Risk Factors” reveals a significant link between early menopause and cognitive decline in women. Researchers from Tohoku University Graduate School of Medicine and Tokyo Metropolitan Institute of Medical Science conducted a study that analyzed the English Longitudinal Study of Ageing, which included 4,726 women and 4,286 men. The team found that women who entered menopause before the age of 40 had worse cognitive outcomes compared to those who entered menopause after the age of 50.

The researchers were motivated by the disproportionate impact of dementia on women worldwide, as well as the association between early menopause and higher risk of depression in later life. The team controlled for modifiable risk factors for dementia and found that menopause at <40 years was significantly associated with worse cognitive function over a two-year follow-up period. Interestingly, the study also showed that hormone replacement therapy (HRT) did not have an association with cognitive function. This suggests that early menopause may be a direct risk factor for cognitive decline in women. The researchers concluded that understanding this relationship could potentially help design treatments to delay the onset of dementia in at-risk patients. The implications of this study are significant, as it highlights the importance of considering sex-specific factors when assessing the risk of developing dementia. Further research is warranted to elucidate the underlying mechanisms of the relationship between levels of female hormones and cognitive function.

Continue Reading

Alzheimer's

Age, Sex, Hormones and Genetics Uncovered: New Clues on Dementia Biomarkers in the Blood

A new study has found important clues about the roles age, sex, hormonal changes and genetics play in how certain biomarkers for dementia are expressed in the blood, according to a new study.

Avatar photo

Published

on

In a groundbreaking study published in Neurology®, researchers have shed light on how age, sex, hormonal changes, and genetics influence certain biomarkers for dementia in the blood. The study, led by Hannah Stocker, PhD, MPH, of Heidelberg University in Germany, provides valuable insights into the roles these factors play in shaping an individual’s risk of developing dementia.

The researchers analyzed data from a larger 17-year study involving 513 people who developed dementia and 513 who remained free of the condition. The participants had an average age of 64 at the start of the study. By taking blood samples three times during the study, the researchers measured levels of three biomarkers: neurofilament light chain proteins, glial acidic proteins, and phosphorylated tau 181.

The findings revealed that older age was associated with higher levels of all three markers. For example, people aged 75 had an average of 25 picograms per milliliter (pg/ml) for neurofilament light chain proteins compared to those aged 50 who averaged 10 pg/ml. Similarly, glial acidic proteins were found at higher levels in older participants, with a significant difference between those aged 75 and those aged 50.

The study also showed that female participants had higher levels of glial acidic proteins, while male participants had higher levels of neurofilament light chain proteins. Furthermore, the researchers discovered that people who carried the APOEe4 gene had higher levels of tau and glial acidic proteins.

Notably, the study found that female participants who had not yet gone through menopause had higher levels of glial acidic proteins. This may be attributed to having higher levels of sex hormones, which have been linked to neuroinflammation in previous studies.

The findings of this study highlight the importance of further exploring these biomarkers, including during menopause, in the development of dementia. By gaining a better understanding of how age, sex, hormonal changes, and genetics interact with biomarker levels, researchers can improve their ability to test for dementia using simple blood tests.

Continue Reading

Alzheimer's Research

Detecting the Invisible: A New Method for Identifying Nanoplastics in Body Fluids

Microplastics and the much smaller nanoplastics enter the human body in various ways, for example through food or the air we breathe. A large proportion is excreted, but a certain amount remains in organs, blood and other body fluids. Scientists have now been able to develop a method for detecting and quantifying nanoplastics in transparent body fluids and determining their chemical composition.

Avatar photo

Published

on

The presence of microplastics and even smaller nanoplastics in our bodies is a growing concern. These tiny particles can enter our system through food, air, or other means, but fortunately, most of them are excreted by our bodies. However, some amount remains lodged in organs, blood, and other bodily fluids. In an effort to understand the impact of nanoplastics on human health, particularly in ophthalmology, a team at Graz University of Technology (TU Graz) has been working on a project called Nano-VISION.

The research team, led by Harald Fitzek from the Institute of Electron Microscopy and Nanoanalysis, in collaboration with an ophthalmologist from Graz and a start-up company named BRAVE Analytics, has successfully developed a method for detecting and quantifying nanoplastics in transparent body fluids. This breakthrough is significant, especially since there have been no studies on intraocular lenses releasing nanoplastics.

The innovative method combines two techniques: optofluidic force induction and Raman spectroscopy. The first technique involves shining a weakly focused laser through the liquid being analyzed, causing particles to accelerate or decelerate based on their size. This allows researchers to determine the concentration of micro- and nanoplastics in the liquid.

What’s new is the addition of Raman spectroscopy, which analyzes the spectrum of the laser light scattered by individual particles in the liquid. Depending on the material composition of these particles, the frequency values are slightly different, revealing their chemical composition. This method works particularly well with organic materials and plastics.

The team at TU Graz has been conducting further investigations into how intraocular lenses yield nanoplastics spontaneously or when exposed to mechanical stress or laser energy. These findings will be crucial for ophthalmic surgeons and lens manufacturers and will be published in a scientific journal.

The implications of this research are far-reaching, not just for the field of ophthalmology but also for industries and our environment. The method developed by this team can be applied to continuously monitor liquid flows in various sectors, from drinking water to waste management.

Continue Reading

Trending