Although offspring of women exposed to childhood trauma exhibit elevated rates of psychopathology, many children demonstrate resilience to these intergenerational impacts. Among the variety of factors that likely contribute to resilience, epigenetic processes have been suggested to play an important role. The current study used a prospective design to test the novel hypothesis that offspring epigenetic aging – a measure of methylation differences that are associated with infant health outcomes – moderates the relationship between maternal exposure to childhood adversity and offspring symptomatology. Maternal childhood adversity was self-reported during pregnancy via the ACEs survey and the CTQ, which assessed total childhood trauma as well as maltreatment subtypes (i.e., emotional, physical, and sexual abuse). Offspring blood samples were collected at or shortly after birth and assayed on a DNA methylation microarray, and offspring symptomatology was assessed with the CBCL/1.5–5 when offspring were 2–4 years old. Results indicated that maternal childhood trauma, particularly sexual abuse, was predictive of offspring symptoms (ps = 0.003–0.03). However, the associations between maternal sexual abuse and offspring symptomatology were significantly attenuated in offspring with accelerated epigenetic aging. These findings further our understanding of how epigenetic processes may contribute to and attenuate the intergenerational link between stress and psychopathology.

Knowledge graphs have become a common approach for knowledge representation. Yet, the application of graph methodology is elusive due to the sheer number and complexity of knowledge sources. In addition, semantic incompatibilities hinder efforts to harmonize and integrate across these diverse sources. As part of The Biomedical Translator Consortium, we have developed a knowledge graph–based question-answering system designed to augment human reasoning and accelerate translational scientific discovery: the Translator system. We have applied the Translator system to answer biomedical questions in the context of a broad array of diseases and syndromes, including Fanconi anemia, primary ciliary dyskinesia, multiple sclerosis, and others. A variety of collaborative approaches have been used to research and develop the Translator system. One recent approach involved the establishment of a monthly “Question-of-the-Month (QotM) Challenge” series. Herein, we describe the structure of the QotM Challenge; the six challenges that have been conducted to date on drug-induced liver injury, cannabidiol toxicity, coronavirus infection, diabetes, psoriatic arthritis, and ATP1A3-related phenotypes; the scientific insights that have been gleaned during the challenges; and the technical issues that were identified over the course of the challenges and that can now be addressed to foster further development of the prototype Translator system. We close with a discussion on Large Language Models such as ChatGPT and highlight differences between those models and the Translator system.

As the COVID-19 pandemic took hold in the USA in early 2020, it became clear that knowledge of the prevalence of antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) among asymptomatic individuals could inform public health policy decisions and provide insight into the impact of the infection on vulnerable populations. Two Clinical and Translational Science Award (CTSA) Hubs and the National Institutes of Health (NIH) set forth to conduct a national seroprevalence survey to assess the infection’s rate of spread. This partnership was able to quickly design and launch the project by leveraging established research capacities, prior experiences in large-scale, multisite studies and a highly skilled workforce of CTSA hubs and unique experimental capabilities at the NIH to conduct a diverse prospective, longitudinal observational cohort of 11,382 participants who provided biospecimens and participant-reported health and behavior data. The study was completed in 16 months and benefitted from transdisciplinary teamwork, information technology innovations, multimodal communication strategies, and scientific partnership for rigor in design and analytic methods. The lessons learned by the rapid implementation and dissemination of this national study is valuable in guiding future multisite projects as well as preparation for other public health emergencies and pandemics.

A multi-disciplinary expert group met to discuss vitamin D deficiency in the UK and strategies for improving population intakes and status. Changes to UK Government advice since the 1st Rank Forum on Vitamin D (2009) were discussed, including rationale for setting a reference nutrient intake (10 µg/d; 400 IU/d) for adults and children (4+ years). Current UK data show inadequate intakes among all age groups and high prevalence of low vitamin D status among specific groups (e.g. pregnant women and adolescent males/females). Evidence of widespread deficiency within some minority ethnic groups, resulting in nutritional rickets (particularly among Black and South Asian infants), raised particular concern. Latest data indicate that UK population vitamin D intakes and status reamain relatively unchanged since Government recommendations changed in 2016. Vitamin D food fortification was discussed as a potential strategy to increase population intakes. Data from dose–response and dietary modelling studies indicate dairy products, bread, hens’ eggs and some meats as potential fortification vehicles. Vitamin D3 appears more effective than vitamin D2 for raising serum 25-hydroxyvitamin D concentration, which has implications for choice of fortificant. Other considerations for successful fortification strategies include: (i) need for ‘real-world’ cost information for use in modelling work; (ii) supportive food legislation; (iii) improved consumer and health professional understanding of vitamin D’s importance; (iv) clinical consequences of inadequate vitamin D status and (v) consistent communication of Government advice across health/social care professions, and via the food industry. These areas urgently require further research to enable universal improvement in vitamin D intakes and status in the UK population.

Mapping weed infestations in an annual crop has implications not only for site-specific herbicide applications but also for planning future management strategies and understanding weed ecology. A controlled laboratory experiment, involving detached leaves, was conducted to investigate the potential to discriminate two crop and five weed species using hyperspectral and multispectral remote sensing. Stepwise discriminant function analyses showed that reflectance in the visible and “red-edge” regions of the spectrum were consistently required for species discrimination. The seven species were correctly identified 90 and 89% of the time using the hyperspectral and multispectral data, respectively, and the classification rules derived from discriminant function analyses. Errant species prediction with the hyperspectral data resulted in a grass being predicted as a grass and a broadleaf as a broadleaf. However, for multispectral data, incorrect classifications were more serious because errant predictions sometimes resulted in a grass being classified as a broadleaf and vice-versa. Further studies using plants at a variety of growth stages, from a variety of environments, and at the canopy level are warranted.

An AMS radiocarbon-dated pollen record from a peat deposit on Mitkof Island, southeastern Alaska provides a vegetation history spanning ∼12,900 cal yr BP to the present. Late Wisconsin glaciers covered the entire island; deglaciation occurred > 15,400 cal yr BP. The earliest known vegetation to develop on the island (∼12,900 cal yr BP) was pine woodland (Pinus contorta) with alder (Alnus), sedges (Cyperaceae) and ferns (Polypodiaceae type). By ∼12,240 cal yr BP, Sitka spruce (Picea sitchensis) began to colonize the island while pine woodland declined. By ∼11,200 cal yr BP, mountain hemlock (Tsuga mertensiana) began to spread across the island. Sitka spruce-mountain hemlock forests dominated the lowland landscapes of the island until ∼10,180 cal yr BP, when western hemlock (Tsuga heterophylla) began to colonize, and soon became the dominant tree species. Rising percentages of pine, sedge, and sphagnum after ∼7100 cal yr BP may reflect an expansion of peat bog habitats as regional climate began to shift to cooler, wetter conditions. A decline in alders at that time suggests that coastal forests had spread into the island's uplands, replacing large areas of alder thickets. Cedars (Chamaecyparis nootkatensis, Thuja plicata) appeared on Mitkof Island during the late Holocene.