A newly sequenced genome of the bacterium that causes syphilis, Treponema pallidum, highlights the deep antiquity of treponemal diseases in the Americas. The findings, based on a 5,500-year-old specimen from Colombia, suggest syphilis’s emergence was not dependent on the agricultural intensification and population crowding often linked to the spread of infectious disease. Instead, it was dependent on social and ecological conditions of hunter-gatherer societies. “Reframing syphilis, alongside other infectious diseases, as products of both localized and highly specific evolutionary, ecological, and biosocial conditions and globalization may represent critical steps toward reducing stigma and improving public health,” write Molly Zuckerman and Lydia Ball in a related perspective. Treponemal diseases, such as syphilis, yaws, bejel, and pinta, have afflicted human populations across much of the world for thousands of years. However, much about the global antiquity and distribution of these diseases, as well as the evolutionary history of the bacteria that cause them, remains unknown. Among the most debated questions is the geographic origin and global spread of syphilis, which is caused by the bacterium T. pallidum. Some argue that the disease originated in the Americas and was brought to the Eastern Hemisphere following European contact in the late 15^th century. Others maintain that Treponema was already present in Europe before contact. Yet the rarity and ambiguity of skeletal evidence of these diseases and the technical difficulty of recovering ancient bacterial DNA from affected remains has made addressing these questions difficult.

 

David Bozzi and colleagues present a 5,500-year-old Treponema genome recovered from Middle Holocene-age human hunter-gatherer remains from Colombia. The new evidence extends the known genetic record of this pathogen by roughly 3,000 years. According to Bozzi et al., phylogenetic analysis shows that this genome (TE1-3) represents a previously unknown branch of T. pallidum that split off before all other known subspecies emerged. Although it falls clearly within the T. pallidum species, TE1-3 is genetically diverse and distinct from modern strains. Notably, the authors found that TE1-3 also carries the full suite of genetic features associated with virulence in modern T. pallidum. Moreover, the findings suggest that T. pallidum predates the rise of agriculture in the Americas, indicating that the pathogen’s emergence was not dependent on the agricultural intensification and population crowding often linked to the spread of infectious disease. Instead, the TE1-3 lineage is associated with the social and ecological conditions of hunter-gatherer societies, including high mobility, small community interactions, and close contact with wild animals. According to Bozzi et al., the study’s findings expand the temporal, ecological, and social framework for understanding treponemal disease worldwide.

In a Policy Forum, Daniel Schroeder and colleagues discuss the risks of malicious “Artificial Intelligence (AI) swarms”, which enable a new class of large-scale, coordinated disinformation campaigns that pose significant risks to democracy. Manipulation of public opinion has long relied on rhetoric and propaganda. However, modern AI systems have created powerful new tools for shaping human beliefs and behavior on a societal scale. Large language models (LLMs) and autonomous agents can now generate vast amounts of persuasive, human-like content. When combined into collaborative AI Swarms – collections of AI-driven personas that retain memory and identity – these systems can mimic social dynamics and easily infiltrate online communities, making false narratives appear credible and widely shared. According to the authors, unlike earlier labor-intensive influence operations run by humans, AI systems can operate cheaply, consistently, and at tremendous scale, transforming once isolated disinformation efforts into persistent, adaptive campaigns that pose serious risks to democratic processes worldwide. Here, Schroeder et al. discuss the technology underpinning these malicious systems and identify pathways through which they can harm democratic discourse through widely used digital platforms. The authors argue that defense against these systems must be layered and pragmatic, aiming not for total prevention of their use, which is highly unlikely, but for raising the cost, risk, and visibility of manipulation. Because such efforts would require global coordination outside of corporate and governmental interests, Schroeder et al. propose a distributed “AI Influence Observatory,” consisting of a network of academic groups, nongovernmental organizations, and other civil institutions to guide independent oversight and action. “Success depends on fostering collaborative action without hindering scientific research while ensuring that the public sphere remains both resilient and accountable,” write the authors. “By committing now to rigorous measurement, proportionate safeguards, and shared oversight, upcoming elections could even become a proving ground for, rather than a setback to, democratic AI governance.”

Artificial intelligence (AI) applied to abdominal imaging can help predict adults at higher risk of falling as early as middle age, a new Mayo Clinic study shows. The research, published in Mayo Clinic Proceedings, highlights the importance of abdominal muscle quality, a component of core strength, as a key predictor of fall risk in adults aged 45 years and older.