Long-duration gamma-ray burst (GRB) afterglow observations offer cutting-edge opportunities to characterise the star formation history of the Universe back to the epoch of reionisation, and to measure the chemical composition of interstellar and intergalactic gas through absorption spectroscopy. The main barrier to progress is the low efficiency in rapidly and confidently identifying which bursts are high redshift ( $z > 5$ ) candidates before they fade, as this requires low-latency follow-up observations at near-infrared wavelengths (or longer) to determine a reliable photometric redshift estimate. Since no current or planned gamma-ray observatories carry near-infrared telescopes on-board, complementary facilities are needed. So far this task has been performed by instruments on the ground, but sky visibility and weather constraints limit the number of GRB targets that can be observed and the speed at which follow-up is possible. In this work we develop a Monte Carlo simulation framework to investigate an alternative approach based on the use of a rapid-response near-infrared nano-satellite, capable of simultaneous imaging in four bands from $0.8$ to $1.7\,\unicode{x03BC}$ m (a mission concept called SkyHopper). Using as reference a sample of 88 afterglows observed with the GROND instrument on the MPG/ESO telescope, we find that such a nano-satellite is capable of detecting in the H-band (1.6 $\unicode{x03BC}$ m) $72.5\% \pm 3.1\%$ of GRBs concurrently observable with the Swift satellite via its UVOT instrument (and $44.1\% \pm 12.3\%$ of high redshift ( $z>5$ ) GRBs) within 60 min of the GRB prompt emission. This corresponds to detecting ${\sim}55$ GRB afterglows per year, of which 1–3 have $z > 5$ . These rates represent a substantial contribution to the field of high-z GRB science, as only 23 $z > 5$ GRBs have been collectively discovered by the entire astronomical community over the last ${\sim}24$ yr. Future discoveries are critically needed to take advantage of next generation follow-up spectroscopic facilities such as 30m-class ground telescopes and the James Webb Space Telescope. Furthermore, a systematic space-based follow-up of afterglows in the near-infrared will offer new insight on the population of dusty (‘dark’) GRBs which are primarily found at cosmic noon ( $z\sim 1-3$ ). Additionally, we find that launching a mini-constellation of 3 near-infrared nano-satellites would increase the detection fraction of afterglows to ${\sim}83\%$ and substantially reduce the latency in the photometric redshift determination.

Maternal experiences of childhood adversity can increase the risk of emotional and behavioural problems in their children. This systematic review and meta-analysis provide the first narrative and quantitative synthesis of the mediators and moderators involved in the link between maternal childhood adversity and children's emotional and behavioural development. We searched EMBASE, PsycINFO, Medline, Cochrane Library, grey literature and reference lists. Studies published up to February 2021 were included if they explored mediators or moderators between maternal childhood adversity and their children's emotional and behavioural development. Data were synthesised narratively and quantitatively by meta-analytic approaches. The search yielded 781 articles, with 74 full-text articles reviewed, and 41 studies meeting inclusion criteria. Maternal mental health was a significant individual-level mediator, while child traumatic experiences and insecure maternal–child attachment were consistent family-level mediators. However, the evidence for community-level mediators was limited. A meta-analysis of nine single-mediating analyses from five studies indicated three mediating pathways: maternal depression, negative parenting practices and maternal insecure attachment, with pooled indirect standardised effects of 0.10 [95% CI (0.03–0.17)), 0.01 (95% CI (−0.02 to 0.04)] and 0.07 [95% CI (0.01–0.12)], respectively. Research studies on moderators were few and identified some individual-level factors, such as child sex (e.g. the mediating role of parenting practices being only significant in girls), biological factors (e.g. maternal cortisol level) and genetic factors (e.g. child's serotonin-transporter genotype). In conclusion, maternal depression and maternal insecure attachment are two established mediating pathways that can explain the link between maternal childhood adversity and their children's emotional and behavioural development and offer opportunities for intervention.

Background: Infection prevention and control (IPC) workflows are often retrospective and manual. New tools, however, have entered the field to facilitate rapid prospective monitoring of infections in hospitals. Although artificial intelligence (AI)–enabled platforms facilitate timely, on-demand integration of clinical data feeds with pathogen whole-genome sequencing (WGS), a standardized workflow to fully harness the power of such tools is lacking. We report a novel, evidence-based workflow that promotes quicker infection surveillance via AI-assisted clinical and WGS data analysis. The algorithm suggests clusters based on a combination of similar minimum inhibitory concentration (MIC) data, timing of sample collection, and shared location stays between patients. It helps to proactively guide IPC professionals during investigation of infectious outbreaks and surveillance of multidrug-resistant organisms and healthcare-acquired infections. Methods: Our team established a 1-year workgroup comprised of IPC practitioners, clinical experts, and scientists in the field. We held weekly roundtables to study lessons learned in an ongoing surveillance effort at a tertiary care hospital—utilizing Philips IntelliSpace Epidemiology (ISEpi), an AI-powered system—to understand how such a tool can enhance practice. Based on real-time case discussions and evidence from the literature, a workflow guidance tool and checklist were codified. Results: In our workflow, data-informed clusters posed by ISEpi underwent triage and expert follow-up analysis to assess: (1) likelihood of transmission(s); (2) potential vector(s) identity; (3) need to request WGS; and (4) intervention(s) to be pursued, if warranted. In a representative sample (spanning October 17, 2019, to November 7, 2019) of 67 total isolates suggested for inclusion in 19 unique cluster investigations, we determined that 9 investigations merited follow-up. Collectively, these 9 investigations involved 21 patients and required 115 minutes to review in ISEpi and an additional 70 minutes of review outside of ISEpi. After review, 6 investigations were deemed unlikely to represent a transmission; the other 3 had potential to represent transmission for which interventions would be performed. Conclusions: This study offers an important framework for adaptation of existing infection control workflow strategies to leverage the utility of rapidly integrated clinical and WGS data. This workflow can also facilitate time-sensitive decisions regarding sequencing of specific pathogens given the preponderance of available clinical data supporting investigations. In this regard, our work sets a new standard of practice: precision infection prevention (PIP). Ongoing effort is aimed at development of AI-powered capabilities for enterprise-level quality and safety improvement initiatives.

Funding: Philips Healthcare provided support for this study.

Disclosures: Alan Doty and Juan Jose Carmona report salary from Philips Healthcare.

Psychotic and psychotic-like experiences (PLEs) are frequently found in the general population when assessed with self-report questionnaires. It is not clear how these assessments can help to predict the future development of mental disorders. The degree of certainty in appraisal or the experience-related distress may add prognostic power of clinical PLE assessments. This study was designed to provide baseline data of PLEs in a representative sample, which will be monitored for the future development.

Uranium–35 wt.% zirconium (U–35 wt.% Zr) alloy was annealed for 1 h and 24 h at 650 °C and characterized to understand the early-stage microstructure evolution. Dendritic microstructure with fine (∼300 nm in length) α-U precipitates clustered between dendrite branches were observed in the 1-h annealed sample. After 24-h annealing at 650 °C, the α-U precipitates coarsened, and the dendritic microstructure disappeared because of microstructure homogenization. Furthermore, microchemical homogenization observed with energy-dispersive X-ray spectroscopy analysis suggests that α-U precipitates are approaching thermodynamic equilibrium in the 24-h annealed sample. The findings from this study have potential impacts on the manufacturing and computer modeling of metallic nuclear fuel.