Thursday December 12, 2019

New Approach for Treating Diseases Like Diabetes and Cancer

Enhanced activation of Vitamin D by protecting beta cells may be a potential new approach for treating diabetes as well as other diseases, including cancer, researchers have suggested.

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The researchers found that Vitamin D in cells and mouse models can be beneficial in treating these damaged beta cells.
Representational image, pixabay

Enhanced activation of Vitamin D by protecting beta cells may be a potential new approach for treating diabetes as well as other diseases, including cancer, researchers have suggested.

When beta cells — the cells in the pancreas that produce, store and release the hormone insulin — become dysfunctional, the body cannot make insulin to control blood sugar (glucose) and levels of glucose can rise to dangerous and even fatal levels.

The researchers found that Vitamin D in cells and mouse models can be beneficial in treating these damaged beta cells.

They also provided new insights about gene regulation that could be applied to developing treatments for other diseases, including cancer.

“We know that diabetes is a disease caused by inflammation. We identified the Vitamin D receptor as an important modulator of both inflammation and beta cell survival,” said Ronald Evans, from Salk Institute for Biological Studies in California, US.

Combining the new compound with vitamin D allowed certain protective genes to be expressed at much higher levels than they are in diseased cells.
Representational image, pixabay

Using beta cells created from embryonic stem cells, the team was able to identify a compound — iBRD9 — that appeared to enhance the activation of the Vitamin D receptor when it was combined with Vitamin D to improve the survival of beta cells.

In the paper, published in the journal Cell, the team conducted a screening test to look for compounds that improved the survival of beta cells in a dish. They then tested the combination in a mouse model of diabetes and showed that it could bring glucose back to normal levels in the animals.

Combining the new compound with vitamin D allowed certain protective genes to be expressed at much higher levels than they are in diseased cells.

“Activating the vitamin D receptor can trigger the anti-inflammatory function of genes to help cells survive under stressed conditions,” explained Michael Downes, from the institute.

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The researchers noted that although the new compound did not appear to cause any side effects in the mice, further testing is needed before clinical trials can begin. (IANS)

Next Story

AI Can Better Help Doctors to Identify Cancer Cells in Human Body

The process of manually identifying all the cells in a pathology slide is extremely labor intensive and error-prone

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Cancer
The AI algorithm helps pathologists obtain the most accurate Cancer cell analysis - in a much faster way. Pixabay

Researchers at University of Texas Southwestern have developed a software tool that uses Artificial Intelligence (AI) to recognize Cancer cells from digital pathology images – giving clinicians a powerful way of predicting patient outcomes.

The spatial distribution of different types of cells can reveal a cancer’s growth pattern, its relationship with the surrounding microenvironment, and the body’s immune response.

But the process of manually identifying all the cells in a pathology slide is extremely labor intensive and error-prone.

“To make a diagnosis, pathologists usually only examine several ‘representative’ regions in detail, rather than the whole slide. However, some important details could be missed by this approach,” said Dr. Guanghua “Andy” Xiao, corresponding author of a study published in EbioMedicine.

A major technical challenge in systematically studying the tumor microenvironment is how to automatically classify different types of cells and quantify their spatial distributions.

The AI algorithm that Dr Xiao and his team developed, called “ConvPath”, overcomes these obstacles by using AI to classify cell types from lung cancer pathology images.

Cancer
Researchers at University of Texas Southwestern have developed a software tool that uses Artificial Intelligence (AI) to recognize Cancer Cells from digital pathology images – giving clinicians a powerful way of predicting patient outcomes. Pixabay

The ConvPath algorithm can “look” at cells and identify their types based on their appearance in the pathology images using an AI algorithm that learns from human pathologists.

The algorithm helps pathologists obtain the most accurate cancer cell analysis – in a much faster way.

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“It is time-consuming and difficult for pathologists to locate very small tumour regions in tissue images, so this could greatly reduce the time that pathologists need to spend on each image,” said Dr Xiao. (IANS)