AI-enabled synthetic biology has tremendous potential but also significantly increases biorisks and brings about a new set of dual use concerns. The picture is complicated given the vast innovations envisioned to emerge by combining emerging technologies, as AI-enabled synthetic biology potentially scales up bioengineering into industrial biomanufacturing. However, the literature review indicates that goals such as maintaining a reasonable scope for innovation, or more ambitiously to foster a huge bioeconomy do not necessarily contrast with biosafety, but need to go hand in hand. This paper presents a literature review of the issues and describes emerging frameworks for policy and practice that transverse the options of command-and-control, stewardship, bottom-up, and laissez-faire governance. How to achieve early warning systems that enable prevention and mitigation of future AI-enabled biohazards from the lab, from deliberate misuse, or from the public realm, will constantly need to evolve, and adaptive, interactive approaches should emerge. Although biorisk is subject to an established governance regime, and scientists generally adhere to biosafety protocols, even experimental, but legitimate use by scientists could lead to unexpected developments. Recent advances in chatbots enabled by generative AI have revived fears that advanced biological insight can more easily get into the hands of malignant individuals or organizations. Given these sets of issues, society needs to rethink how AI-enabled synthetic biology should be governed. The suggested way to visualize the challenge at hand is whack-a-mole governance, although the emerging solutions are perhaps not so different either.

The role of early child care experiences on the development of the mother-child attachment relationship has been studied extensively. However, no prospective studies of early child care have addressed how these experiences might be reflected in the content of attachment representations during adolescence and beyond. The goal of this study was to estimate relatively precise associations between child care quality, child care quantity, and type of care in the first 54 months of life and the content of adolescents\' attachment representations around age 18 years (N = 857; 51% female; 78% White, non-Hispanic; M income-to-needs ratio = 4.13), leveraging data from the longitudinal NICHD Study of Early Child Care and Youth Development (SECCYD). We identified a small positive association between the observed quality of early child care (but not quantity or type of care) and secure attachment states of mind as measured by the Adult Attachment Interview (but not the Attachment Script Assessment) at age 18 years that was robust to demographic covariates and observations of maternal and paternal sensitivity during childhood. We observed no significant interactions among child care variables. Associations between early child care experiences and indicators of adolescent attachment were likewise not moderated by maternal sensitivity from infancy to mid-adolescence or by maternal reports of child temperament in early childhood.

A large body of evidence has shown that stress throughout life is associated with health trajectories, but the combination of adverse experiences at different stages of the life course is not yet well understood. This study examines the interactions between childhood adversity, adulthood adversity, and adult physical and mental health. Using data from The Childhood Retrospective Circumstances Study (CRCS) supplement to the Panel Study of Income Dynamics (PSID), we created indices of early life adversity (EAI) and adult adversity (AAI). We used logistic regression to examine the effects of EAI and AAI, adjusting for age, sex, race/ethnicity, health behaviors, and childhood health as covariates in all models. We repeated this analysis for the outcomes of fair/poor health, two or more chronic conditions, and psychological distress in adulthood. For all the three outcomes, our findings suggest increasing salience of adult adversity among those who experienced higher levels of early adversity. Individuals with high EAI and high AAI exhibited the highest odds of fair/poor health (OR = 5.71), chronic conditions (OR = 3.06), and psychological distress (OR = 13.08) compared to those with low EAI and low AAI. These findings are consistent with the accumulation of risk or dual risk model of stress and health. Adversity in childhood amplifies the health risks associated with stress in adulthood for multiple health outcomes.