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.

A consensus workshop on low-calorie sweeteners (LCS) was held in November 2018 where seventeen experts (the panel) discussed three themes identified as key to the science and policy of LCS: (1) weight management and glucose control; (2) consumption, safety and perception; (3) nutrition policy. The aims were to identify the reliable facts on LCS, suggest research gaps and propose future actions. The panel agreed that the safety of LCS is demonstrated by a substantial body of evidence reviewed by regulatory experts and current levels of consumption, even for high users, are within agreed safety margins. However, better risk communication is needed. More emphasis is required on the role of LCS in helping individuals reduce their sugar and energy intake, which is a public health priority. Based on reviews of clinical evidence to date, the panel concluded that LCS can be beneficial for weight management when they are used to replace sugar in products consumed in the diet (without energy substitution). The available evidence suggests no grounds for concerns about adverse effects of LCS on sweet preference, appetite or glucose control; indeed, LCS may improve diabetic control and dietary compliance. Regarding effects on the human gut microbiota, data are limited and do not provide adequate evidence that LCS affect gut health at doses relevant to human use. The panel identified research priorities, including collation of the totality of evidence on LCS and body weight control, monitoring and modelling of LCS intakes, impacts on sugar reduction and diet quality and developing effective communication strategies to foster informed choice. There is also a need to reconcile policy discrepancies between organisations and reduce regulatory hurdles that impede low-energy product development and reformulation.

This study aimed to examine the influence of the complexity of the story-book on caregiver extra-textual talk (i.e., interactions beyond text reading) during shared reading with preschool-age children. Fifty-three mother–child dyads (3;00–4;11) were video-recorded sharing two ostensibly similar picture-books: a simple story (containing no false belief) and a complex story (containing a false belief central to the plot, which provided content that was more challenging for preschoolers to understand). Book-reading interactions were transcribed and coded. Results showed that the complex stories facilitated more extra-textual talk from mothers, and a higher quality of extra-textual talk (as indexed by linguistic richness and level of abstraction). Although the type of story did not affect the number of questions mothers posed, more elaborative follow-ups on children's responses were provided by mothers when sharing complex stories. Complex stories may facilitate more and linguistically richer caregiver extra-textual talk, having implications for preschoolers’ developing language abilities.

Online self-reported 24-h dietary recall systems promise increased feasibility of dietary assessment. Comparison against interviewer-led recalls established their convergent validity; however, reliability and criterion-validity information is lacking. The validity of energy intakes (EI) reported using Intake24, an online 24-h recall system, was assessed against concurrent measurement of total energy expenditure (TEE) using doubly labelled water in ninety-eight UK adults (40–65 years). Accuracy and precision of EI were assessed using correlation and Bland–Altman analysis. Test–retest reliability of energy and nutrient intakes was assessed using data from three further UK studies where participants (11–88 years) completed Intake24 at least four times; reliability was assessed using intra-class correlations (ICC). Compared with TEE, participants under-reported EI by 25 % (95 % limits of agreement −73 % to +68 %) in the first recall, 22 % (−61 % to +41 %) for average of first two, and 25 % (−60 % to +28 %) for first three recalls. Correlations between EI and TEE were 0·31 (first), 0·47 (first two) and 0·39 (first three recalls), respectively. ICC for a single recall was 0·35 for EI and ranged from 0·31 for Fe to 0·43 for non-milk extrinsic sugars (NMES). Considering pairs of recalls (first two v. third and fourth recalls), ICC was 0·52 for EI and ranged from 0·37 for fat to 0·63 for NMES. EI reported with Intake24 was moderately correlated with objectively measured TEE and underestimated on average to the same extent as seen with interviewer-led 24-h recalls and estimated weight food diaries. Online 24-h recall systems may offer low-cost, low-burden alternatives for collecting dietary information.

Two separate experiments were conducted in 2015 and 2016 in Citra, FL to investigate the effects of preplant application timing of 2,4-D and dicamba on sesame stand and yield. Nonlinear regression analysis was performed to determine the application timing that caused 10% stand or yield reduction (GR10) compared to the nontreated control (NTC) and expressed as d before planting (DBP; longer intervals indicate more injury). Likewise, regression analysis was used to determine sesame stand that resulted in 10% yield reduction (YR10) expressed as plants m−1 row. Stand measured 3 wk after planting (WAP) revealed 2,4-D applied at 0.53 kg ae ha−1 to be the least injurious treatment to sesame stand (GR10=6.4 DBP). Conversely, dicamba at 1.12 kg ha−1 produced a GR10 of 15.7 DBP for sesame stand at 3 WAP. 2,4-D applied at 0.53 and 1.06 kg ha−1 and dicamba applied at 0.56 kg ha−1 had the lowest GR10 for yield of 2, 3.7, and 3 DBP, respectively. Dicamba applied at 1.12 kg ha−1 proved to be the most injurious treatment to yield, which produced a GR10 value of 10.3 DBP. To simulate possible stand losses associated with dicamba or 2,4-D and the subsequent effect on yield, a separate experiment was conducted in which sesame was thinned to various plant densities and yield was recorded to determine the relationship between plant stand and seed yield. The regression analysis of these data was then compared to that of the experiment treated with 2,4-D and dicamba to separate any physiological effects of the herbicides that would lead to yield reduction from yield effects due to stand loss only. Rate constants were compared and no statistical differences were detected between herbicide and non-herbicide treatments, suggesting that yield reductions that occur from preplant applications of 2,4-D and dicamba were purely due to stand reductions.

Two experiments were conducted in 2015 at multiple locations in Florida to evaluate the effects of planting depth and application timing on S-metolachlor injury in sesame. In both studies, sesame responded negatively to increases in S-metolachlor rate. Altering sesame planting depth did not provide increased safety to PRE S-metolachlor applications. Sesame establishment declined with increased planting depth, likely because of the physical inability of the small seed to emerge from the 3.8-cm depth. Delaying applications of S-metolachlor by 3 or 6 d after planting (DAP) consistently improved sesame establishment. Applications 3 and 6 DAP resulted in 89 to 92% seedling emergence at 2 wk after planting (WAP), relative to 55 to 63% emergence when S-metolachlor was applied the day of planting (0 DAP) or 3 days before (−3 DAP), respectively. Applications 3 DAP resulted in 21 and 2% plant stunting when evaluated 3 and 6 WAP, respectively, whereas all other timings caused 25 to 51% stunting. Yield was reduced 22 and 33% by the −3 DAP and 0 DAP application timings, respectively, whereas no reduction in yield was observed by the delayed application timings. Therefore, delaying applications of S-metolachlor by 3 to 6 days will likely result in improved sesame seedling establishment and total seed yield.

A newly designed, 100 mm2, silicon drift detector has been installed on an aberration-corrected scanning transmission electron microscope equipped with an ultra-high resolution pole piece, without requiring column modifications. With its unique, windowless design, the detector’s active region is in close proximity to the sample, resulting in a dramatic increase in count rate, while demonstrating an increased sensitivity to low energy X-rays and a muted tilt dependence. Numerous examples of X-ray energy dispersive spectrometry are presented on relevant materials such as Al x Ga1−x N nanowires, perovskite oxides, and polycrystalline CdTe thin films, across both varying length scales and accelerating voltages.

Extended abstract of a paper presented at Microscopy and Microanalysis 2013 in Indianapolis, Indiana, USA, August 4 – August 8, 2013.