Corn (Zea mays L.) is an important crop that contributes to global food security, but understanding how farm management practices and soil health affect corn grain nutrient analysis and therefore human health is lacking. Leveraging Rodale Institute's Farming Systems Trial—a long-term field experiment established in 1981 in Kutztown, PA, USA—this study was conducted to assess the impact of different agricultural management systems on corn grain nutrient profiles in a long-term trial that has resulted in differences in soil health indicators between treatments as a result of long-term management. The main plot factor was two tillage practices (intensive and reduced) and the subplot factor was four cropping systems (non-diversified conventional [nCNV], diversified conventional [dCNV], legume-based organic [ORG-LEG], and manure-based organic [ORG-MNR]). Generally, the levels of amino acids, vitamins, and protein in corn grain were greatest in the ORG-MNR system, followed by the ORG-LEG and dCNV systems, and finally the nCNV system. It is important to consider that the observed difference between the organic and conventionally grown grain could be due to variations in corn hybrids that were used in those systems. However, nutrient composition of corn differed within cropping systems but between management practices (diversified crop rotation and cover cropping) which also contributed to differences in soil health indicators (soil compaction, soil protein, and organic C levels) that may also influence grain nutrient concentrations. With the exception of methionine, nutrient concentration in corn grain was not affected by different tillage regimes. These findings provide novel information on corn grain nutritional quality of organic and conventional cropping systems after long-term management and give insights into how system-specific components affect nutrient composition of corn grain.

The concept of interaction classes (iClasses) for multi-environment trial data was introduced to address the problem of summarising variety performance across environments in the presence of variety by environment interaction (VEI). The approach involves the fitting of a factor analytic linear mixed model (FALMM), with the resultant estimates of factor loadings being used to form groups of environments (iClasses) that discriminate varieties with different patterns of VEI. It is then meaningful to summarise variety performance across environments within iClasses. The iClass methodology was developed with respect to a FALMM in which the genetic effects for different varieties were assumed independent. This was done for pedagogical reasons but it was pointed out that the accuracy of variety selection is greatly enhanced by considering the genetic relatedness of varieties, either via ancestral or genomic information. The focus of the current paper is therefore to extend the iClass approach for FALMMs which incorporate such information. In addition a measure of stability of variety performance across iClasses is defined. The utility of the approach for variety selection is illustrated using a multi-environment trial dataset from the lentil breeding program operated by Agriculture Victoria.

In May 2017, whole-genome sequencing (WGS) became the primary subtyping method for Salmonella in Canada. As a result of the increased discriminatory power provided by WGS, 16 multi-jurisdictional outbreaks of Salmonella associated with frozen raw breaded chicken products were identified between 2017 and 2019. The majority (15/16) were associated with S. enteritidis, while the remaining outbreak was associated with S. Heidelberg. The 16 outbreaks included a total of 487 cases with ages ranging from 0 to 98 years (median: 24 years); 79 hospitalizations and two deaths were reported. Over the course of the outbreak investigations, 14 frozen raw breaded chicken products were recalled, and one was voluntarily withdrawn from the market. After previous changes to labelling and the issuance of public communication for these products proved ineffective at reducing illnesses, new industry requirements were issued in 2019, which required the implementation of measures at the manufacturing/processing level to reduce Salmonella to below detectable amounts in frozen raw breaded chicken products. Since implementation, no further outbreaks of Salmonella associated with frozen breaded chicken have been identified in Canada, a testament to the effectiveness of these risk mitigation measures.

The financial burden of hospitalization from life-threatening infectious diseases on the U.S. healthcare system is substantial and continues to increase. The purpose of this study was to identify key predictors of high hospital charges for infective endocarditis at a major university-affiliated cardiac care centre in West Virginia.

A retrospective electronic medical records’ review was undertaken of all adult patients admitted for endocarditis between 2014–2018. Multiple linear regression analysis assessed the total charges billed to the patient account for their endocarditis hospitalization in the medical record.

Hospital charges have increased 12-fold during 2014–2018. Among the 486 patients, the median hospital charge was $198 678. About 47% of the patients underwent surgery incurring 70% of the total charges. Patients with hospital stays of ≥50 days accounted for a third of all charges. The multiple linear regression model accounted for 85% of the linear variance in the hospital charges. Median charges increased by 30.87% for patients with ≥9 consultations, 60.32% for those who died in the hospital, and 81.85% for those who underwent surgical intervention.

The study findings showed that complex care requiring multiple consultations, surgical interventions, and longer hospital stays were significantly associated with higher hospital charges for endocarditis treatment.

The global population and status of Snowy Owls Bubo scandiacus are particularly challenging to assess because individuals are irruptive and nomadic, and the breeding range is restricted to the remote circumpolar Arctic tundra. The International Union for Conservation of Nature (IUCN) uplisted the Snowy Owl to “Vulnerable” in 2017 because the suggested population estimates appeared considerably lower than historical estimates, and it recommended actions to clarify the population size, structure, and trends. Here we present a broad review and status assessment, an effort led by the International Snowy Owl Working Group (ISOWG) and researchers from around the world, to estimate population trends and the current global status of the Snowy Owl. We use long-term breeding data, genetic studies, satellite-GPS tracking, and survival estimates to assess current population trends at several monitoring sites in the Arctic and we review the ecology and threats throughout the Snowy Owl range. An assessment of the available data suggests that current estimates of a worldwide population of 14,000–28,000 breeding adults are plausible. Our assessment of population trends at five long-term monitoring sites suggests that breeding populations of Snowy Owls in the Arctic have decreased by more than 30% over the past three generations and the species should continue to be categorised as Vulnerable under the IUCN Red List Criterion A2. We offer research recommendations to improve our understanding of Snowy Owl biology and future population assessments in a changing world.

Excluding all animal-sourced foods may be associated with increased risks of nutrient deficiencies. As indispensable amino acids (IAAs) cannot be stored or endogenously produced, consistent protein consumption throughout the day is important to improve protein quality for optimal metabolic function(1). Assessment of protein adequacy needs to be undertaken at the meal rather than daily intake level because food combinations within each meal can be complementary and influence the overall amino acid profile of the meal(2).

Outcomes of our previous review found that among plant-sourced foods, soy, legumes, nuts and seeds provide greater protein content and quality(3). We hypothesise that variation in protein intake will exist both between vegan individuals and between observation days for the same individuals. Previous investigations of the relationship between meals and nutrient intake based on specified time windows for eating may have been subject to researcher bias in the definition of these windows. The main outcome of this study is to utilise time series clustering to determine the impact of dietary patterns on protein distribution, across the day.

Intake data was obtained using a four-day food diary from a cross-sectional survey of 193 New Zealand vegans (Ethical approval: HDEC 2022 EXP 12312). The inclusion criteria required participants to have followed an exclusive vegan diet for at least two years. A kernel density contour estimation was used to visualise protein distribution across eating occasions for all participants over four days. Dynamic Time Warping (DTW) was then used to align two temporal sequences (time series) to compute an output of distance(4) which was used for hierarchical clustering using the Ward.D2 method. An optimal cluster of 3 was identified using silhouette coefficient and domain knowledge.

Participants had a mean age of 39.4 years (SD=12.3), with 90.1% having attained a tertiary-level education or higher. Overall, mean protein intake was 1.11 g/kg/d (SD=0.39), with 8.29% of participants below the Estimated Average Requirements (EAR) and 24.3% of participants below the Recommended Dietary Allowance (RDA) for adults. The mean Acceptable Macronutrient Distribution Range (AMDR) for protein is 15.5% (SD=4.16), with 96.9% of participants within the recommended AMDR range (10-35%). Peak protein consumption was observed at 1230 and 1900. Sequential colour scale representing density found higher distribution of data points representing protein intake of less than 10g per eating occasion. Time series similar in shape and amplitude were assigned to the same cluster. Preliminary findings identified three different protein intake profiles across the day.

A small percentage of participants has protein intake below the daily requirements for adults. More occasions with lower protein intake per eating moment was observed. This approach classifies dietary patterns objectively for analysis of daily protein and IAA intake.

We present the Pilot Survey Phase 2 data release for the Wide-field ASKAP L-band Legacy All-sky Blind surveY (WALLABY), carried-out using the Australian SKA Pathfinder (ASKAP). We present 1760 H i detections (with a default spatial resolution of 30′′) from three pilot fields including the NGC 5044 and NGC 4808 groups as well as the Vela field, covering a total of $\sim 180$ deg$^2$ of the sky and spanning a redshift up to $z \simeq 0.09$. This release also includes kinematic models for over 126 spatially resolved galaxies. The observed median rms noise in the image cubes is 1.7 mJy per 30′′ beam and 18.5 kHz channel. This corresponds to a 5$\sigma$ H i column density sensitivity of $\sim 9.1\times10^{19}(1 + z)^4$ cm$^{-2}$ per 30′′ beam and $\sim 20$ km s$^{-1}$ channel and a 5$\sigma$ H i mass sensitivity of $\sim 5.5\times10^8 (D/100$ Mpc)$^{2}$ M$_{\odot}$ for point sources. Furthermore, we also present for the first time 12′′ high-resolution images (“cut-outs”) and catalogues for a sub-sample of 80 sources from the Pilot Survey Phase 2 fields. While we are able to recover sources with lower signal-to-noise ratio compared to sources in the Public Data Release 1, we do note that some data quality issues still persist, notably, flux discrepancies that are linked to the impact of side lobes associated with the dirty beams due to inadequate deconvolution. However, in spite of these limitations, the WALLABY Pilot Survey Phase 2 has already produced roughly a third of the number of HIPASS sources, making this the largest spatially resolved H i sample from a single survey to date.

Herbicide drift to sensitive crops can result in significant injury, yield loss, and even crop destruction. When pesticide drift is reported to the Georgia Department of Agriculture (GDA), tissue samples are collected and analyzed for residues. Seven field studies were conducted in 2020 and 2021 in cooperation with the GDA to evaluate the effect of (1) time interval between simulated drift event and sampling, (2) low-dose herbicide rates, and (3) the sample collection methods on detecting herbicide residues in cotton (Gossypium hirsutum L.) foliage. Simulated drift rates of 2,4-D, dicamba, and imazapyr were applied to non-tolerant cotton in the 8- to 9-leaf stage with plant samples collected at 7 or 21 d after treatment (DAT). During collection, plant sampling consisted of removing entire plants or removing new growth occurring after the 7-leaf stage. Visual cotton injury from 2,4-D reached 43% to 75% at 0.001 and 0.004 kg ae ha−1, respectively; for dicamba, it was 9% to 41% at 0.003 or 0.014 kg ae ha−1, respectively; and for imazapyr, it was 1% to 74% with 0.004 and 0.03 kg ae ha−1 rates, respectively. Yield loss was observed with both rates of 2,4-D (11% to 51%) and with the high rate of imazapyr (52%); dicamba did not influence yield. Herbicide residues were detected in 88%, 88%, and 69% of samples collected from plants treated with 2,4-D, dicamba, and imazapyr, respectively, at 7 DAT compared with 25%, 16%, and 22% when samples were collected at 21 DAT, highlighting the importance of sampling quickly after a drift event. Although the interval between drift event and sampling, drift rate, and sampling method can all influence residue detection for 2,4-D, dicamba, and imazapyr, the factor with the greatest influence is the amount of time between drift and sample collection.

The dissemination and implementation (D&I) of evidence at the community level is critical to improve health and advance health equity. Social networks are considered essential to D&I efforts, but there lacks clarity regarding how best to study and leverage networks. We examined networks in community-level D&I frameworks to characterize the range of network actors, activities, and change approaches. We conducted a narrative review of 66 frameworks. Among frameworks that explicitly addressed networks – that is, elaborated on network characteristics, structure, and/or activities – we extracted and synthesized network concepts using descriptive statistics and narrative summaries. A total of 24 (36%) frameworks explicitly addressed networks. Commonly included actors were implementers, adopters/decision-makers, innovation developers, implementation support professionals, and innovation recipients. Network activities included the exchange of resources, knowledge, trust, and norms. Most network-explicit frameworks characterized ties within and across organizations and considered element(s) of network structure – for example, size, centrality, and density. The most common network change strategy was identifying individuals to champion D&I efforts. We discuss opportunities to expand network inquiry in D&I science, including understanding networks as implementation determinants, leveraging network change approaches as implementation strategies, and exploring network change as an implementation outcome.

Oceania is currently facing a substantial challenge: to provide sustainable and ethical food systems that support nutrition and health across land and water. The Nutrition Society of Australia and the Nutrition Society of New Zealand held a joint 2023 Annual Scientific Meeting on ‘Nutrition and Wellbeing in Oceania’ attended by 408 delegates. This was a timely conference focussing on nutrition challenges across the Pacific, emphasising the importance of nutrition across land and water, education settings, women’s health and gut health. Cutting-edge, multi-disciplinary and collaborative research was presented in a 4-day programme of keynote presentations, workshops, oral and poster sessions, breakfast and lunch symposiums and early career researcher sessions. The conference highlighted the importance of collaboration between nations to address the challenge facing nutrition and wellbeing across Oceania. A systems approach of collaboration among scientists, industry and government is vital for finding solutions to this challenge.