Vascular rings represent a heterogeneous set of aberrant great vessel anatomic configurations which can cause respiratory symptoms or dysphagia due to tracheal or oesophageal compression. These symptoms can be subtle and may present at varied ages. More recently, many have been identified in patients without symptoms, including fetal echocardiogram, resulting in a conundrum for practitioners when attempting to determine who will benefit from surgical correction. Here, we provide a review of vascular rings and a guide to the practitioner on when to consider additional imaging or referral. Additionally, we discuss the changing landscape regarding asymptomatic patients and fetal echocardiogram.

There is a growing focus on understanding the complexity of dietary patterns and how they relate to health and other factors. Approaches that have not traditionally been applied to characterise dietary patterns, such as latent class analysis and machine learning algorithms, may offer opportunities to characterise dietary patterns in greater depth than previously considered. However, there has not been a formal examination of how this wide range of approaches has been applied to characterise dietary patterns. This scoping review synthesised literature from 2005 to 2022 applying methods not traditionally used to characterise dietary patterns, referred to as novel methods. MEDLINE, CINAHL and Scopus were searched using keywords including latent class analysis, machine learning and least absolute shrinkage and selection operator. Of 5274 records identified, 24 met the inclusion criteria. Twelve of twenty-four articles were published since 2020. Studies were conducted across seventeen countries. Nine studies used approaches with applications in machine learning, such as classification models, neural networks and probabilistic graphical models, to identify dietary patterns. The remaining studies applied methods such as latent class analysis, mutual information and treelet transform. Fourteen studies assessed associations between dietary patterns characterised using novel methods and health outcomes, including cancer, cardiovascular disease and asthma. There was wide variation in the methods applied to characterise dietary patterns and in how these methods were described. The extension of reporting guidelines and quality appraisal tools relevant to nutrition research to consider specific features of novel methods may facilitate consistent reporting and enable synthesis to inform policies and programs.

The recommended first-line treatment for insomnia is cognitive behavioral therapy for insomnia (CBTi), but access is limited. Telehealth- or internet-delivered CBTi are alternative ways to increase access. To date, these intervention modalities have never been compared within a single study. Further, few studies have examined a) predictors of response to the different modalities, b) whether successfully treating insomnia can result in improvement of health-related biomarkers, and c) mechanisms of change in CBTi. This protocol was designed to compare the three CBTi modalities to each other and a waitlist control for adults aged 50-65 years (N = 100). Participants are randomly assigned to one of four study arms: in-person- (n=30), telehealth- (n=30) internet-delivered (n=30) CBTi, or 12-week waitlist control (n=10). Outcomes include self-reported insomnia symptom severity, polysomnography, circadian rhythms of activity and core body temperature, blood- and sweat-based biomarkers, cognitive functioning, and magnetic resonance imaging.

Foliar-applied postemergence applications of glufosinate are often applied to glufosinate-resistant crops to provide nonselective weed control without significant crop injury. Rainfall, air temperature, solar radiation, and relative humidity near the time of application have been reported to affect glufosinate efficacy. However, previous research may have not captured the full range of weather variability to which glufosinate may be exposed before or following application. Additionally, climate models suggest more extreme weather will become the norm, further expanding the weather range to which glufosinate can be exposed. The objective of this research was to quantify the probability of successful weed control (efficacy ≥85%) with glufosinate applied to some key weed species across a broad range of weather conditions. A database of >10,000 North American herbicide evaluation trials was used in this study. The database was filtered to include treatments with a single postemergence application of glufosinate applied to waterhemp [Amaranthus tuberculatus (Moq.) Sauer], morningglory species (Ipomoea spp.), and/or giant foxtail (Setaria faberi Herrm.) <15 cm in height. These species were chosen because they are well represented in the database and listed as common and troublesome weed species in both corn (Zea mays L.) and soybean [Glycine max (L.) Merr.] (Van Wychen 2020, 2022). Individual random forest models were created. Low rainfall (≤20 mm) over the 5 d before glufosinate application was detrimental to the probability of successful control of A. tuberculatus and S. faberi. Lower relative humidity (≤70%) and solar radiation (≤23 MJ m−1 d−1) on the day of application reduced the probability of successful weed control in most cases. Additionally, the probability of successful control decreased for all species when average air temperature over the first 5 d after application was ≤25 C. As climate continues to change and become more variable, the risk of unacceptable control of several common species with glufosinate is likely to increase.

Galaxy Zoo is an online project to classify morphological features in extra-galactic imaging surveys with public voting. In this paper, we compare the classifications made for two different surveys, the Dark Energy Spectroscopic Instrument (DESI) imaging survey and a part of the Kilo-Degree Survey (KiDS), in the equatorial fields of the Galaxy And Mass Assembly (GAMA) survey. Our aim is to cross-validate and compare the classifications based on different imaging quality and depth. We find that generally the voting agrees globally but with substantial scatter, that is, substantial differences for individual galaxies. There is a notable higher voting fraction in favour of ‘smooth’ galaxies in the DESI+zoobot classifications, most likely due to the difference between imaging depth. DESI imaging is shallower and slightly lower resolution than KiDS and the Galaxy Zoo images do not reveal details such as disc features and thus are missed in the zoobot training sample. We check against expert visual classifications and find good agreement with KiDS-based Galaxy Zoo voting. We reproduce the results from Porter-Temple+ (2022), on the dependence of stellar mass, star formation, and specific star formation on the number of spiral arms. This shows that once corrected for redshift, the DESI Galaxy Zoo and KiDS Galaxy Zoo classifications agree well on population properties. The zoobot cross-validation increases confidence in its ability to compliment Galaxy Zoo classifications and its ability for transfer learning across surveys.

Foliar-applied postemergence herbicides are a critical component of corn (Zea mays L.) and soybean [Glycine max (L.) Merr.] weed management programs in North America. Rainfall and air temperature around the time of application may affect the efficacy of herbicides applied postemergence in corn or soybean production fields. However, previous research utilized a limited number of site-years and may not capture the range of rainfall and air temperatures that these herbicides are exposed to throughout North America. The objective of this research was to model the probability of achieving successful weed control (≥85%) with commonly applied postemergence herbicides across a broad range of environments. A large database of more than 10,000 individual herbicide evaluation field trials conducted throughout North America was used in this study. The database was filtered to include only trials with a single postemergence application of fomesafen, glyphosate, mesotrione, or fomesafen + glyphosate. Waterhemp [Amaranthus tuberculatus (Moq.) Sauer], morningglory species (Ipomoea spp.), and giant foxtail (Setaria faberi Herrm.) were the weeds of focus. Separate random forest models were created for each weed species by herbicide combination. The probability of successful weed control deteriorated when the average air temperature within the first 10 d after application was <19 or >25 C for most of the herbicide by weed species models. Additionally, drier conditions before postemergence herbicide application reduced the probability of successful control for several of the herbicide by weed species models. As air temperatures increase and rainfall becomes more variable, weed control with many of the commonly used postemergence herbicides is likely to become less reliable.

Palmer amaranth (Amaranthus palmeri S. Watson, AMAPA) is one of the most troublesome weeds in North America due to its rapid growth rate, substantial seed production, competitiveness and the evolution of herbicide-resistant populations. Though frequently encountered in the South, Midwest, and Mid-Atlantic regions of the United States, A. palmeri was recently identified in soybean [Glycine max (L.) Merr.] fields in Genesee, Orange, and Steuben counties, NY, where glyphosate was the primary herbicide for in-crop weed control. This research, conducted in 2023, aimed to (1) describe the dose response of three putative resistant NY A. palmeri populations to glyphosate, (2) determine their mechanisms of resistance, and (3) assess their sensitivity to other postemergence herbicides commonly used in NY crop production systems. Based on the effective dose necessary to reduce aboveground biomass by 50% (ED50), the NY populations were 42 to 67 times more resistant to glyphosate compared with a glyphosate-susceptible population. Additionally, the NY populations had elevated EPSPS gene copy numbers ranging from 25 to 135 located within extrachromosomal circular DNA (eccDNA). Label rate applications of Weed Science Society of America (WSSA) Group 2 herbicides killed up to 42% of the NY populations of A. palmeri. Some variability was observed among populations in response to WSSA Group 5 and 27 herbicides. All populations were effectively controlled by labeled rates of herbicides belonging to WSSA Groups 4, 10, 14, and 22. Additional research is warranted to confirm whether NY populations have evolved multiple resistance to herbicides within other WSSA groups and to develop effective A. palmeri management strategies suitable for NY crop production.

This manuscript addresses a critical topic: navigating complexities of conducting clinical trials during a pandemic. Central to this discussion is engaging communities to ensure diverse participation. The manuscript elucidates deliberate strategies employed to recruit minority communities with poor social drivers of health for participation in COVID-19 trials. The paper adopts a descriptive approach, eschewing analysis of data-driven efficacy of these efforts, and instead provides a comprehensive account of strategies utilized. The Accelerate COVID-19 Treatment Interventions and Vaccines (ACTIV) public–private partnership launched early in the COVID-19 pandemic to develop clinical trials to advance SARS-CoV-2 treatments. In this paper, ACTIV investigators share challenges in conducting research during an evolving pandemic and approaches selected to engage communities when traditional strategies were infeasible. Lessons from this experience include importance of community representatives’ involvement early in study design and implementation and integration of well-developed public outreach and communication strategies with trial launch. Centralization and coordination of outreach will allow for efficient use of resources and the sharing of best practices. Insights gleaned from the ACTIV program, as outlined in this paper, shed light on effective strategies for involving communities in treatment trials amidst rapidly evolving public health emergencies. This underscores critical importance of community engagement initiatives well in advance of the pandemic.

Cereal rye (Secale cereale L.) cover crop and preemergence herbicides are important components of an integrated weed management program for waterhemp [Amaranthus tuberculatus (Moq.) Sauer] and Palmer amaranth (Amaranthus palmeri S. Watson) management in soybean [Glycine max (L.) Merr.]. Accumulating adequate cereal rye biomass for effective suppression of Amaranthus spp. can be challenging in the upper Midwest due to the short window for cereal rye growth in a corn–soybean rotation. Farmers are adopting the planting green system to optimize cereal rye biomass production and weed suppression. This study aimed to evaluate the feasibility of planting soybean green when integrated with preemergence herbicides for the control of Amaranthus spp. under two soybean planting time frames. The study was conducted across 19 site-years in the United States over the 2021 and 2022 growing seasons. Factors included cover crop management practices (“no-till,” “cereal rye early-term,” and “cereal rye plant-green”), soybean planting times (“early” and “late”), and use of preemergence herbicides (“NO PRE” and “YES PRE”). Planting soybean green increased cereal rye biomass production by 33% compared with early termination. Greater cereal rye biomass production when planting green provided a 44% reduction in Amaranthus spp. density compared with no-till. The use of preemergence herbicides also resulted in a 68% reduction in Amaranthus spp. density compared with NO PRE. Greater cereal rye biomass produced when planting green reduced soybean stand, which directly reduced soybean yield in some site-years. Planting soybean green is a feasible management practice to optimize cereal rye biomass production, which, combined with preemergence herbicides, provided effective Amaranthus spp. management. Soybean stand was a key factor in maintaining soybean yields compared with no-till when planting green. Farmers should follow best management recommendations for proper planter and equipment setup to ensure effective soybean establishment under high levels of cereal rye biomass when planting green.

We present the second data release for the GaLactic and Extragalactic All-sky Murchison Widefield Array eXtended (GLEAM-X) survey. This data release is an area of 12 892-deg$^2$ around the South Galactic Pole region covering 20 h40 m$\leq$RA$\leq$6 h40 m, -90$^\circ$$\leq$Dec$\leq$+30$^\circ$. Observations were taken in 2020 using the Phase-II configuration of the Murchison Widefield Array (MWA) and covering a frequency range of 72–231 MHz with twenty frequency bands. We produce a wideband source finding mosaic over 170–231 MHz with a median root-mean-squared noise of $1.5^{+1.5}_{-0.5}$ mJy beam$^{-1}$. We present a catalogue of 624 866 components, including 562 302 components which are spectrally fit. This catalogue is 98% complete at 50 mJy, and a reliability of 98.7% at a 5 $\sigma$ level, consistent with expectations for this survey. The catalogue is made available via Vizier, and the PASA datastore and accompanying mosaics for this data release are made available via AAO Data Central and SkyView.

Background: Early identification of patients colonized with MDROs can help healthcare facilities improve infection control and treatment. We evaluated whether a model previously validated to predict carbapenem-resistant Enterobacterales (CRE) carriage on hospital admission (area under the curve [AUC]=0.86, Lin et al. OFID 2019) would generalize to predict a patient’s likelihood of CRE and non-CRE MDRO colonization at the time of medical intensive care unit (MICU) admission. Methods: We analyzed data collected previously in a retrospective observational cohort study of patients admitted to Rush University Medical Center’s MICU from 1/2017-1/2018 and screened within the first two days for rectal MDRO colonization. Organisms of interest included CRE, carbapenem-resistant Pseudomonas aeruginosa (CRPA), vancomycin-resistant enterococci (VRE), and third-generation cephalosporin-resistant Enterobacterales (3GCR-E). Methicillin-resistant Staphylococcus aureus (MRSA) nasal colonization at admission was determined by routine clinical screening. Each patient’s first MICU admission during the study period was linked to Illinois’ hospital discharge database and assigned a CRE colonization risk probability using the existing model. Model covariates were age, and during the prior 365 days, number of short-term acute care hospitalizations (STACH) and mean STACH length of stay, number of long-term acute care hospitalizations (LTACH) and mean LTACH length of stay, prior hospital admission with an ICD-10 diagnosis code indicating bacterial infection, and current admission to LTACH. Predictive value of the model was evaluated by receiver operating characteristic (ROC) curves. Results: We analyzed 1237 MICU admissions. MDRO admission prevalence is shown in the Table. The model performed well to predict carriage of healthcare-associated MDROs, including CRE, CRPA, composite CR-MDROs (CRE & CRPA), and VRE. However, the model performed poorly for MDROs with known community reservoirs, including 3GCR-E and MRSA (Table). In general, MDRO admission prevalence increased in parallel with predicted CRE colonization risk (Figure). The number needed to screen (NNS) to detect one healthcare-associated MDRO carrier was inversely related to the CRE colonization risk score. For example, NNS in the total cohort compared to those with CRE risk score of >0.5% was: CRE 111 vs 32 patients, CRPA 333 vs 42 patients, composite CR-MDRO 83 vs 18 patients, and VRE 12 vs 4 patients. However, higher CRE risk score cutoff was inversely related to screening sensitivity. Conclusion: A prediction model using prior healthcare exposure information successfully discriminated patients likely to harbor healthcare-associated MDROs upon MICU admission. Prediction scores generated by a public-health accessible database could be used to target screening/isolation or enact protective measures for high-risk patients.

If livestock at risk of poor welfare could be identified using a risk assessment tool, more targeted response strategies could be developed by enforcement agencies to facilitate early intervention, prompt welfare improvement and a decrease in reoffending. This study aimed to test the ability of an Animal Welfare Risk Assessment Tool (AWRAT) to identify livestock at risk of poor welfare in extensive farming systems in Australia. Following farm visits for welfare- and non-welfare-related reasons, participants completed a single welfare rating (WR) and an assessment using the AWRAT for the farm just visited. A novel algorithm was developed to generate an AWRAT-Risk Rating (AWRAT-RR) based on the AWRAT assessment. Using linear regression, the relationship between the AWRAT-RR and the WR was tested. The AWRAT was good at identifying farms with poor livestock welfare based on this preliminary testing. As the AWRAT relies upon observation, the intra- and inter-observer agreement were compared in an observation study. This included rating a set of photographs of farm features, on two occasions. Intra-observer reliability was good, with 83% of Intra-class Correlation Coefficients (ICCs) for observers ≥ 0.8. Inter-observer reliability was moderate with an ICC of 0.67. The AWRAT provides a structured framework to improve consistency in livestock welfare assessments. Further research is necessary to determine the AWRAT’s ability to identify livestock at risk of poor welfare by studying animal welfare incidents and reoffending over time.

The objective of this study was to identify factors more commonly observed on farms with poor livestock welfare compared to farms with good welfare. Potentially, these factors may be used to develop an animal welfare risk assessment tool (AWRAT) that could be used to identify livestock at risk of poor welfare. Identifying livestock at risk of poor welfare would facilitate early intervention and improve strategies to promptly resolve welfare issues. This study focuses on cattle, sheep and goats in non-dairy extensive farming systems in Australia. To assist with identifying potential risk factors, a survey was developed presenting 99 factors about the farm, farmers, animals and various aspects of management. Based on their experience, key stakeholders, including veterinarians, stock agents, consultants, extension and animal welfare officers were asked to consider a farm where the welfare of the livestock was either high or low and rate the likelihood of observing these factors. Of the 141 responses, 65% were for farms with low welfare. Only 6% of factors had ratings that were not significantly different between high and low welfare surveys, and these were not considered further. Factors from poor welfare surveys with median ratings in the lowest 25% were considered potential risks (n = 49). Considering correlation, ease of verification and the different livestock farming systems in Australia, 18 risk factors relating to farm infrastructure, nutrition, treatment and husbandry were selected. The AWRAT requires validation in future studies.

Autoimmune encephalitis is increasingly recognized as a neurologic cause of acute mental status changes with similar prevalence to infectious encephalitis. Despite rising awareness, approaches to diagnosis remain inconsistent and evidence for optimal treatment is limited. The following Canadian guidelines represent a consensus and evidence (where available) based approach to both the diagnosis and treatment of adult patients with autoimmune encephalitis. The guidelines were developed using a modified RAND process and included input from specialists in autoimmune neurology, neuropsychiatry and infectious diseases. These guidelines are targeted at front line clinicians and were created to provide a pragmatic and practical approach to managing such patients in the acute setting.