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From cancer detection to treatment, how AI is transforming health care

From cancer detection to treatment, how AI is transforming health care

Artificial intelligence is changing the DNA of health care with the promise of a 'healthier human'. The second of a three-part series
Shelley Singh New Delhi
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In early 2024, Marly Garnreiter, a 27-year-old French woman, began experiencing persistent night sweats and itchy skin. Her doctors dismissed it as stress. Her blood report came back normal. Out of curiosity, she asked ChatGPT about it. The artificial intelligence (AI) chatbot suggested she might have blood cancer. Nearly a year later, in April 2025, doctors confirmed she had Hodgkin's lymphoma, a cancer that affects the lymphatic system.
Stories like Garnreiter's are making headlines repeatedly: AI catching what humans miss.
While anecdotal, they point to a shift underway in health care — one where AI doesn't replace doctors but sharpens
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The French biochemist Jacques Monod (1910-1976), who won a Nobel Prize in 1965 for discovering how cells regulate the expression of genes, famously said, 'What is true for Escherichia coli is true for the elephant.' He meant the same fundamental mechanisms of molecular biology, such as protein synthesis, DNA replication, and cellular metabolism, are shared by both bacteria and elephants. In his comment, Monod was taking a bird's-eye view of biology. If you zoomed in enough, two bacterial cells with identical genomes — and even from the same colony — can be quite different from each other. One cell might express a particular gene at a high level while the other might express it at a low level or not at all. Each bacterium goes on to transmit its expression level to its offspring in a process called epigenetic inheritance. Such variations among otherwise identical cells and organisms is called bistability. 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To test this, the team cultured mouse immune cells and infected them with P. aeruginosa bacteria containing the GFP fusion gene. Team members found that the bacteria that came in contact with macrophage cells of the mouse immune system fluoresced more brightly, meaning glpD was being expressed more. Playing it safe The variability in the expression levels of the glpD expression was evident even in small clusters of around 10-50 cells. Given that cells that produced more glpD transcripts were better at setting infections in motion suggested that an infection can be initiated by even a small group. As the researchers wrote in their paper, 'varying levels of glpD expression … might be a strategy … for the success of P. aeruginosa as an opportunistic pathogen'. Axiomatically, a drug targeting this variation could prevent P. aeruginosa from being the scourge it currently is in hospitals. D.P. Kasbekar is a retired scientist.

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