Knee osteoarthritis isn’t inevitable — here’s what you can do - Science Daily
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Scientists Uncover a New Biological Driver of Osteoarthritis - ScienceAlert
Osteoarthritis, where the cartilage in a joint gradually erodes away and leads to the painful friction of bone-on-bone, is the leading cause of disability for older adults worldwide. Until now, it's also been considered a consequence of mechanical wear and tear. Researchers led by a team from Chonnam National University in South Korea have come up with an alternative hypothesis: What if high blood pressure (hypertension) could also be contributing to the breakdown of cartilage tissue? In a new study in Science, the researchers make the connection between the hormone arginine vasopressin (AVP), which is more abundant in people with hypertension, and its receptor AVPR1A – essentially a lock on the surface of cells that enables AVP to trigger a chemical reaction. While AVPR1A is barely present in healthy cartilage, it begins to appear more as we get older or after an injury. That essentially primes the cartilage for AVP interactions, the researchers suggest, which then triggers chemical reactions that degrade the tissue.

Managing Knee Osteoarthritis Across the Lifespan - EMJ
LIFELONG physical activity and targeted strength training preserve joint integrity while reducing overall knee osteoarthritis risk. In young adults between 20 and 30 years of age, articular cartilage maintains peak resilience through dynamic cyclic loading. Walking for 10 minutes stimulates interstitial fluid pressurization and nutrient influx, restoring compressed tissue thickness three times faster than supine rest. However, clinicians must actively counsel young athletes on acute injury prevention. Anterior cruciate ligament ruptures peak before age 25, predisposing nearly half of affected patients to posttraumatic joint degeneration within ten years. Diagnostic vigilance must also account for normal baseline variance. A systematic review of imaging of asymptomatic knees in adults under 40 reveals cartilage defects in 11% and meniscal tears in 4%, demonstrating that incidental structural irregularities do not necessarily warrant clinical alarm.

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Integrating hippopotamus optimization algorithm into machine learning frameworks for predicting suspended sediment concentrations - Nature
ORCID: orcid.org/0000-0001-8061-88361, Yaser Mehri2, Ali Abdolrazaq Sabbar3, Mohammad Javad Nahvinia3 & … Mohammad Hosein Omid2 We’re sharing this article early to provide faster access to peer-reviewed, accepted research. It is citable and carries a permanent DOI. This version is subject to further edits and will be replaced automatically by the final Version of Record. All legal disclaimers apply.
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