Cervical cancer is a major threat to women's health. Multimodal fusion AI models integrate cytological, histopathological, clinical, and molecular data, potentially improving detection sensitivity, grading accuracy, and screening efficiency. Traditional methods face limitations in subjectivity, efficiency, and primary care resources. This review details the technical architecture, fusion strategies (deep learning, attention mechanisms, cross‑modal alignment), clinical applications, and translational challenges of multimodal fusion AI models. With further refinement and validation, these models may become useful tools for improving cervical cancer screening and prevention.

Adolescence is a critical time for nutritional health, given the rapid physical growth, hormonal changes, and neurodevelopmental shifts taking place. Yet diet quality is at its lowest during this pivotal life stage, which is compounded by unique physiological, social, and behavioral factors facing adolescents. In fact, public health guidance has noted that nutrient gaps among adolescents set the stage for a “constellation of potential nutritional risk factors.”¹ This public health challenge is exacerbated by the lack of scientific research and specific, evidence-based dietary guidance tailored to adolescents. To elevate awareness of this issue and identify research needs, the Arkansas Children’s Nutrition Center (ACNC) partnered with the National Cattlemen’s Beef Association, on behalf of the Beef Checkoff, to convene Nourish Now: A Science Dialogue on Improving Adolescent Health through Nutrition, including 50 leading nutrition scientists, previous Dietary Guidelines Advisory Committee members, physicians, registered dietitians, and public health experts. Two manuscripts from this convening have now been published in Critical Reviews in Food Science and Nutrition: Proceedings from Nourish Now: A science dialogue on improving adolescent health through nutrition; and Call to action: the future of evidence-based, adolescent-focused dietary guidance.

Amaranth, an underutilised pseudocereal, can yield bioactive peptides with antioxidant, antimicrobial, ACE‑inhibitory, DPP‑IV‑inhibitory, anti‑inflammatory, antithrombotic, and anticancer activities in preclinical models. However, translation is limited by low bioavailability, extraction challenges, incomplete sequence identification, and scarce clinical validation. This review summarises production methods, reported bioactivities, and future research priorities. Evidence supports potential, but clinical efficacy is not established. Future work requires optimised extraction, structure‑activity characterisation, in vivo studies, and clinical trials.