Got lower back pain? Walk it off!; Oncogenes aid neural-circuit growth; Six subtypes of depression, anxiety identified – Morning Medical Update

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Got lower back pain? Walk it off!

A new study from The Lancet that adults who had a history of lower-back pain and walked regularly went twice as long between recurrences of pain, compared to those who did not walk regularly.

Mark Hancock, PhD, a senior author of the study and a professor of physiotherapy at Macquarie University, said, “We don’t know exactly why walking is so good for preventing back pain, but it is likely to include the combination of the gentle oscillatory movements, loading and strengthening the spinal structures and muscles, relaxation and stress relief, and release of ‘feel-good’ endorphins.”

With these new results, experts believe that walking can provide a cost-effective and accessible therapy to treat lower back pain. Read more about the study here.

Oncogenes aid neural-circuit growth

Oncogenes are typically known to be the genes involved in different cancers in humans, such as the gene “Src.” However, what’s less understood is that these genes didn’t evolve just to cause cancer. In fact, oncogenes evolve to control events of normal growth and differentiation in the body as well.

Erik Lundquist, professor of molecular biosciences and associate vice chancellor for research at the University of Kansas, recently published new research that showed what Src does in a normal development context. Lundquist and his colleagues from his lab used a model organism called C. elegans, a nematode word whose Src gene is very similar to human, to track the development of the nervous system.

The results showed that the gene plays a key role in development of the nervous system by guiding axons. You can find out more of the potential of oncogenes aiding neural-circuit growth in this article.

Six subtypes of depression, anxiety identified

Brain imaging paired with artificial intelligence (AI) has identified six subtypes of depression and anxiety, which has the potential to lead to more personalized and effective treatment.

Using cluster analysis, a machine learning technique, to group patients’ brain images, researchers identified these subtypes by analyzing specific profiles of dysfunction within both task-free and task-evoked brain circuits.

While the biotypes have not been named, these findings provide more understanding of the neurobiological causes of depression and anxiety. Find out more about this new discovery in psychology here.