Thursday April 2, 2020

Few Kinds of Cancer Drugs May Be Helpful in Treating Lung Inflammation: Study

The research discovered that specific cancer drugs inhibit a cell signalling process controlling the death-rate of the harmful neutrophils

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Lungs
The research discovered that specific cancer drugs inhibit a cell signalling process controlling the death-rate of the harmful neutrophils. Pixabay

Certain class of cancer drugs could be used in the future to treat chronic obstructive pulmonary disease (COPD), say researchers, adding that the drugs could be developed to stop the progression of the disease and promote healing within the lungs.

COPD makes breathing progressively more difficult for millions of people around the world, and the study, published in the journal eLIFE has shown the potential for clinically available cancer treatments to treat it.

“COPD is usually treated with steroids and airway muscle relaxants which ease symptoms, but there is currently no effective treatment clinically available to counteract the damage it does to the lungs,” said study researcher Lynne Prince from the University of Sheffield in UK.

“Our research now shows that inhibitors of these cell signalling processes, or ErbB kinases, could have therapeutic potential in neutrophilic inflammatory disease,” Prince added. Accroding to the researchers, the hope of these drugs is that they can clear the damaging cells from the lungs of people living with COPD, preventing any further damage and therefore the progression of the disease for the first time.

They have been investigating the effect of drugs used to treat a variety of cancers on this inflammatory response; the main driver of lung damage in people living with COPD. People living with COPD experience a wide range of symptoms that have an increasing impact on their quality of life, including breathlessness, coughing and frequent chest infections.

The damage to the lungs is driven by inflammation caused by immune cells called neutrophils. For the results, the research team screened a library of cancer drugs and identified a number of compounds which accelerate the death of the neutrophil cells and promote healing in the lungs.

Cancer
Certain class of cancer drugs could be used in the future to treat chronic obstructive pulmonary disease (COPD), say researchers, adding that the drugs could be developed to stop the progression of the disease and promote healing within the lungs. Pixabay

The research discovered that specific cancer drugs inhibit a cell signalling process controlling the death-rate of the harmful neutrophils. The team also discovered that editing the genes that encode the cell signalling in the first place, further decreased inflammation.

“As neutrophilic inflammation is also central to the progression of other chronic inflammatory diseases such as rheumatoid arthritis, the research has the potential to impact not only people living with COPD,” said study researcher Stephen Renshaw from the University of Sheffield in UK.

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“Our next step is to find a way to test these drugs in people with COPD to understand how the ErbB kinase signalling process has an effect on lung inflammation and to address any potential side effects,” Renshaw added. (IANS)

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Researchers Develop AI Algorithm That Can Diagnose Skin Diseases

The researchers caution that AI cannot definitively interpret images, that it is not trained to interpret even when the problem presented is straightforward

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AI
Recently, there have been remarkable advances in the use of AI in medicine. Pixabay

Researchers have developed a deep learning-based artificial intelligence (AI) algorithm that can accurately classify cutaneous skin disorders, predict malignancy, suggest primary treatment options, and serve as an ancillary tool to enhance the diagnostic accuracy of clinicians. With the assistance of this system, the diagnostic accuracy of dermatologists, as well as the general public, was significantly improved, said the study, published in the Journal of Investigative Dermatology.

Skin diseases are common, but it is not always easy to visit a dermatologist quickly or distinguish malignant from benign conditions. “Recently, there have been remarkable advances in the use of AI in medicine. For specific problems, such as distinguishing between melanoma and nevi, AI has shown results comparable to those of human dermatologists,” said lead investigator Jung-Im Na from Seoul National University in South Korea. Most prior studies have been limited to specific binary tasks, such as differentiating melanoma from nevi.

“Our results suggest that our algorithm may serve as an Augmented Intelligence that can empower medical professionals in diagnostic dermatology,” Na added.

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Using a “convolutional neural network,” a specialised AI algorithm, the research team developed an AI system capable of predicting malignancy, suggesting treatment options, and classifying skin disorders. They collected 220,000 images of Asians and Caucasians with 174 skin diseases and trained neural networks to interpret those images.

AI
Researchers have developed a deep learning-based artificial intelligence (AI) algorithm that can accurately classify cutaneous skin disorders. Pixabay

They found that the algorithm could diagnose 134 skin disorders and suggest primary treatment options, render multi-class classification among disorders, and enhance the performance of medical professionals through Augmented Intelligence.”Rather than AI replacing humans, we expect AI to support humans as Augmented Intelligence to reach diagnoses faster and more accurately,” Na said.

The researchers caution that AI cannot definitively interpret images, that it is not trained to interpret even when the problem presented is straightforward. For example, an algorithm trained only to differentiate between melanoma and nevi cannot differentiate between an image of a nail hematoma and either a melanoma or a nevus. If the shape of the hematoma is irregular, the algorithm may diagnose it as melanoma.

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They also pointed out that the algorithm was trained and tested using high-quality images and its performance is generally suboptimal if the input images are of low quality. “We anticipate that the use of our algorithm with a smartphone could encourage the public to visit specialists for cancerous lesions such as melanoma that might have been neglected otherwise, however, there are issues with the quality or composition of photographs taken by the general public that may affect the results of the algorithm, Na said. (IANS)