Spatial variations in aromatic hydrocarbon emission in a dust-rich galaxy.

Dust grains absorb half of the radiation emitted by stars throughout the history of the universe, re-emitting this energy at infrared wavelengths1-3. Polycyclic aromatic hydrocarbons (PAHs) are large organic molecules that trace millimetre-size dust grains and regulate the cooling of interstellar gas within galaxies4,5. Observations of PAH features in very distant galaxies have been difficult owing to the limited sensitivity and wavelength coverage of previous infrared telescopes6,7. Here we present James Webb Space Telescope observations that detect the 3.3 µm PAH feature in a galaxy observed less than 1.5 billion years after the Big Bang. The high equivalent width of the PAH feature indicates that star formation, rather than black hole accretion, dominates infrared emission throughout the galaxy. The light from PAH molecules, hot dust and large dust grains and stars are spatially distinct from one another, leading to order-of-magnitude variations in PAH equivalent width and ratio of PAH to total infrared luminosity across the galaxy. The spatial variations we observe suggest either a physical offset between PAHs and large dust grains or wide variations in the local ultraviolet radiation field. Our observations demonstrate that differences in emission from PAH molecules and large dust grains are a complex result of localized processes within early galaxies.

Reintroducing face-to-face support alongside remote support to form a hybrid stop smoking service in England: a formative mixed methods evaluation.

BACKGROUND: During the COVID-19 pandemic, United Kingdom (UK) stop smoking services had to shift to remote delivery models due to social distancing regulations, later reintroducing face-to-face provision. The "Living Well Smokefree" service in North Yorkshire County Council adopted a hybrid model offering face-to-face, remote, or a mix of both. This evaluation aimed to assess the hybrid approach's strengths and weaknesses and explore potential improvements. METHODS: Conducted from September 2022 to February 2023, the evaluation consisted of three components. First, qualitative interviews involved 11 staff and 16 service users, analysed thematically. Second, quantitative data from the QuitManager system that monitored the numbers and proportions of individuals selecting and successfully completing a 4-week quit via each service option. Third, face-to-face service expenses data was used to estimate the value for money of additional face-to-face provision. The qualitative findings were used to give context to the quantitative data via an "expansion" approach and complementary analysis. RESULTS: Overall, a hybrid model was seen to provide convenience and flexible options for support. In the evaluation, 733 individuals accessed the service, with 91.3% selecting remote support, 6.1% face-to-face, and 2.6% mixed provision. Remote support was valued by service users and staff for promoting openness, privacy, and reducing stigma, and was noted as removing access barriers and improving service availability. However, the absence of carbon monoxide monitoring in remote support raised accountability concerns. The trade-off in "quantity vs. quality" of quits was debated, as remote support reached more users but produced fewer carbon monoxide-validated quits. Primarily offering remote support could lead to substantial workloads, as staff often extend their roles to include social/mental health support, which was sometimes emotionally challenging. Offering service users a choice of support options was considered more important than the "cost-per-quit". Improved dissemination of information to support service users in understanding their options for support was suggested. CONCLUSIONS: The hybrid approach allows smoking cessation services to evaluate which groups benefit from remote, face-to-face, or mixed options and allocate resources accordingly. Providing choice, flexible provision, non-judgmental support, and clear information about available options could improve engagement and match support to individual needs, enhancing outcomes.

Coherent terahertz laser feedback interferometry for hydration sensing in leaves.

The response of terahertz to the presence of water content makes it an ideal analytical tool for hydration monitoring in agricultural applications. This study reports on the feasibility of terahertz sensing for monitoring the hydration level of freshly harvested leaves of Celtis sinensis by employing a imaging platform based on quantum cascade lasers and laser feedback interferometry. The imaging platform produces wide angle high resolution terahertz amplitude and phase images of the leaves at high frame rates allowing monitoring of dynamic water transport and other changes across the whole leaf. The complementary information in the resulting images was fed to a machine learning model aiming to predict relative water content from a single frame. The model was used to predict the change in hydration level over time. Results of the study suggest that the technique could have substantial potential in agricultural applications.

Phenological optimization of late reproductive phase for raising wheat yield potential in irrigated mega-environments.

Increasing grain number through fine-tuning duration of the late reproductive phase (LRP; terminal spikelet to anthesis) without altering anthesis time has been proposed as a genetic strategy to increase yield potential (YP) of wheat. Here we conducted a modelling analysis to evaluate the potential of fine-tuning LRP in raising YP in irrigated mega-environments. Using the known optimal anthesis and sowing date of current elite benchmark genotypes, we applied a gene-based phenology model for long-term simulations of phenological stages and yield-related variables of all potential germplasm with the same duration to anthesis as the benchmark genotypes. These diverse genotypes had the same duration to anthesis but varying LRP duration. Lengthening LRP increased YP and harvest index by increasing grain number to some extent and an excessively long LRP reduced YP due to reduced time for canopy construction for high biomass production of pre-anthesis phase. The current elite genotypes could have their LRP extended for higher YP in most sites. Genotypes with a ratio of the duration of LRP to pre-anthesis phase of about 0.42 ensured high yields (≥95% of YP) with their optimal sowing and anthesis dates. Optimization of intermediate growth stages could be further evaluated in breeding programmes to improve YP.

Integrating a crop growth model and radiative transfer model to improve estimation of crop traits based on deep learning.

A major challenge for the estimation of crop traits (biophysical variables) from canopy reflectance is the creation of a high-quality training dataset. To address this problem, this research investigated a conceptual framework by integrating a crop growth model with a radiative transfer model to introduce biological constraints in a synthetic training dataset. In addition to the comparison of two datasets without and with biological constraints, we also investigated the effects of observation geometry, retrieval method, and wavelength range on estimation accuracy of four crop traits (leaf area index, leaf chlorophyll content, leaf dry matter, and leaf water content) of wheat. The theoretical analysis demonstrated potential advantages of adding biological constraints in synthetic training datasets as well as the capability of deep learning. Additionally, the predictive models were validated on real unmanned aerial vehicle-based multispectral images collected from wheat plots contrasting in canopy structure. The predictive model trained over a synthetic dataset with biological constraints enabled the prediction of leaf water content from using wavelengths in the visible to near infrared range based on the correlations between crop traits. Our findings presented the potential of the proposed conceptual framework in simultaneously retrieving multiple crop traits from canopy reflectance for applications in precision agriculture and plant breeding.

Comparison of 3-factor versus 4-factor prothrombin complex concentrate for emergent warfarin reversal: a systematic review and meta-analysis.

BACKGROUND: Patients requiring emergent warfarin reversal (EWR) have been prescribed three-factor prothrombin complex concentrate (PCC3) and four-factor prothrombin complex concentrate (PCC4) to reverse the anticoagulant effects of warfarin. There is no existing systematic review and meta-analysis of studies directly comparing PCC3 and PCC4. METHODS: The primary objective of this systematic review and meta-analysis was to determine the effectiveness of achieving study defined target INR goal after PCC3 or PCC4 administration. Secondary objectives were to determine the difference in safety endpoints, thromboembolic events (TE), and survival during the patients' hospital stay. Random-effects meta-analysis models were used to estimate the odds ratios (OR), and heterogeneity associated with the outcomes. The Newcastle-Ottawa Scale was used to assess study quality, and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. RESULTS: Ten full-text manuscripts and five abstracts provided data for the primary and secondary outcomes. Patients requiring EWR had more than three times the odds of reversal to goal INR when they were given PCC4 compared to PCC3 (OR = 3.61, 95% CI: 1.97-6.60, p < 0.001). There was no meaningful clinical association or statistically significant result between PCC4 and PCC3 groups in TE (OR = 1.56, 95% CI: 0.83-2.91, p = 0.17), or survival during hospital stay (OR = 1.34, 95% CI: 0.81-2.23, p = 0.25). CONCLUSION: PCC4 is more effective than PCC3 in meeting specific predefined INR goals and has similar safety profiles in patients requiring emergent reversal of the anticoagulant effects of warfarin.

Concomitant Marked Decline in Prevalence of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) and Other Respiratory Viruses Among Symptomatic Patients Following Public Health Interventions in Australia: Data from St Vincent's Hospital and Associated Screening Clinics, Sydney, NSW.

Our Australian hospital tested almost 22 000 symptomatic people over 11 weeks for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in a multiplex polymerase chain reaction (PCR) assay. Following travel bans and physical distancing, SARS-CoV-2 and other respiratory viruses diagnoses fell dramatically. Increasing rhinovirus diagnoses as social control measures were relaxed may indirectly indicate an elevated risk of coronavirus disease 2019 (COVID-19) resurgence.

Using a gene-based phenology model to identify optimal flowering periods of spring wheat in irrigated mega-environments.

To maximize the grain yield of spring wheat, flowering needs to coincide with the optimal flowering period (OFP) by minimizing frost and heat stress on reproductive development. This global study conducted a comprehensive modelling analysis of genotype, environment, and management to identify the OFPs for sites in irrigated mega-environments of spring wheat where the crop matures during a period of increasing temperatures. We used a gene-based phenology model to conduct long-term simulation analysis with parameterized genotypes to identify OFPs and optimal sowing dates for sites in irrigated mega-environments, considering the impacts of frost and heat stress on yield. The validation results showed that the gene-based model accurately predicted wheat heading dates across global wheat environments. The long-term simulations indicated that frost and heat stress significantly advanced or delayed OFPs and shrank the durations of OFPs in irrigated mega-environments when compared with OFPs where the model excluded frost and heat stress impacts. The simulation results (incorporating frost and heat penalties on yield) also showed that earlier flowering generally resulted in higher yields, and early sowing dates and/or early flowering genotypes were suggested to achieve early flowering. These results provided an interpretation of the regulation of wheat flowering to the OFP by the selection of sowing date and cultivar to achieve higher yields in irrigated mega-environments.

Scaling up high-throughput phenotyping for abiotic stress selection in the field.

KEY MESSAGE: High-throughput phenotyping (HTP) is in its infancy for deployment in large-scale breeding programmes. With the ability to measure correlated traits associated with physiological ideotypes, in-field phenotyping methods are available for screening of abiotic stress responses. As cropping environments become more hostile and unpredictable due to the effects of climate change, the need to characterise variability across spatial and temporal scales will become increasingly important. The sensor technologies that have enabled HTP from macroscopic through to satellite sensors may also be utilised here to complement spatial characterisation using envirotyping, which can improve estimations of genotypic performance across environments by better accounting for variation at the plot, trial and inter-trial levels. Climate change is leading to increased variation at all physical and temporal scales in the cropping environment. Maintaining yield stability under circumstances with greater levels of abiotic stress while capitalising upon yield potential in good years, requires approaches to plant breeding that target the physiological limitations to crop performance in specific environments. This requires dynamic modelling of conditions within target populations of environments, GxExM predictions, clustering of environments so breeding trajectories can be defined, and the development of screens that enable selection for genetic gain to occur. High-throughput phenotyping (HTP), combined with related technologies used for envirotyping, can help to address these challenges. Non-destructive analysis of the morphological, biochemical and physiological qualities of plant canopies using HTP has great potential to complement whole-genome selection, which is becoming increasingly common in breeding programmes. A range of novel analytic techniques, such as machine learning and deep learning, combined with a widening range of sensors, allow rapid assessment of large breeding populations that are repeatable and objective. Secondary traits underlying radiation use efficiency and water use efficiency can be screened with HTP for selection at the early stages of a breeding programme. HTP and envirotyping technologies can also characterise spatial variability at trial and within-plot levels, which can be used to correct for spatial variations that confound measurements of genotypic values. This review explores HTP for abiotic stress selection through a physiological trait lens and additionally investigates the use of envirotyping and EC to characterise spatial variability at all physical scales in METs.

Characteristics and outcomes of patients with peripheral artery disease undergoing endovascular revascularization: A community hospital perspective.

BACKGROUND: There are limited data on outcomes for patients with peripheral artery disease undergoing endovascular revascularization by multi-disciplinary teams in a community hospital setting. METHODS: From January 2015 through December 2015, we assembled a multi-disciplinary program comprised of cardiologists, surgeons, radiologists, nurses, and administrative staff for managing patients with peripheral artery disease undergoing endovascular revascularization. Demographic, procedural, and outcomes data were collected with use of a template from the Society for Vascular Surgery Vascular Quality Initiative database. We compared characteristics and outcomes of patients with intermittent claudication and critical limb ischemia. We used Kaplan-Meier methods to estimate the rate of overall survival and freedom from rehospitalization between groups. RESULTS: After excluding patients with acute limb ischemia (n = 5), peripheral intervention to the upper extremity (n = 6), or abdominal aorta (n = 11), there were 82 patients in the study cohort; 45 had intermittent claudication and 37 had critical limb ischemia. Baseline and procedural characteristics were similar between groups, although critical limb ischemia patients were more likely to have hyperlipidemia (75.7% vs. 53.3%, P = .42). Procedural success was achieved in 91.3% of cases. Actionable access site bleeding occurred in 2.4% of patients. High rates of aspirin (91.5%) and statin (87.8%) were noted at discharge. After two years of post endovascular revascularization, survival was 57.5% for critical limb ischemia patients and 94.4% for intermittent claudication patients (P < .001). Freedom from rehospitalization was 32.7% for critical limb ischemia patients and 83.5% for intermittent claudication patients (P < .001). CONCLUSIONS: We found that favorable outcomes may be achieved with a multi-disciplinary peripheral artery disease program at community hospitals. The incorporation of quality improvement practices may further help to develop standardized and regionalized approaches to care delivery for patients with peripheral artery disease.

CT Three-Dimensional (3D) Modeling Maintains Fluoroscopy Time and Contrast Volume to a Minimum in the Endovascular Treatment of Great Vessel Injury from Iatrogenic Trauma.

CT angiography with multislice detector has become the preferred method for assessment of hemodynamically stable patients suspected of great vessel injury from iatrogenic and blunt trauma. The CT images obtained can be transformed into a three-dimensional (3D) model using the software within minutes. This allows the clinician to evaluate the injury and the injury's proximity to other vital structures for operative planning. The 3D modeling provides geometric calibration of the c-arm or image intensifier in regard to optimal cranial/caudal and oblique angles to evaluate and treat the vessel injury. We describe a case of a 28-year-old female undergoing a cesarian section and hysterectomy for placenta percreta, who sustained a right subclavian artery injury (presumed wire injury) from inadvertent right common carotid artery cannulation during placement of a right internal jugular 8 French resuscitative central line. A 3D model was created from the CT angiography to locate the small pseudoaneurysm of the right subclavian artery. The optimal projection was obtained using the 3D reconstructive software to visualize the injury and its relation to the right vertebral artery ostium for endovascular planning. This preoperative maneuver allowed for limited radiation exposure and contrast volume used to treat the injury.

Australian and New Zealand consensus statement on the management of lymphoma, chronic lymphocytic leukaemia and myeloma during the COVID-19 pandemic.

The COVID-19 pandemic poses a unique challenge to the care of patients with haematological malignancies. Viral pneumonia is known to cause disproportionately severe disease in patients with cancer, and patients with lymphoma, myeloma and chronic lymphocytic leukaemia are likely to be at particular risk of severe disease related to COVID-19. This statement has been developed by consensus among authors from Australia and New Zealand. We aim to provide supportive guidance to clinicians making individual patient decisions during the COVID-19 pandemic, in particular during periods that access to healthcare resources may be limited. General recommendations include those to minimise patient exposure to COVID-19, including the use of telehealth, avoidance of non-essential visits and minimisation of time spent by patients in infusion suites and other clinical areas. This statement also provides recommendations where appropriate in assessing indications for therapy, reducing therapy-associated immunosuppression and reducing healthcare utilisation in patients with specific haematological malignancies during the COVID-19 pandemic. Specific decisions regarding therapy of haematological malignancies will need to be individualised, based on disease risk, risks of immunosuppression, rates of community transmission of COVID-19 and available local healthcare resources.

Propensity score adjusted comparison of three-factor versus four-factor prothrombin complex concentrate for emergent warfarin reversal: a retrospective cohort study.

BACKGROUND: Prothrombin Complex Concentrates (PCC) are prescribed for emergent warfarin reversal (EWR). The comparative effectiveness and safety among PCC products are not fully understood. METHODS: Patients in an academic level one trauma center who received PCC3 or PCC4 for EWR were identified. Patient characteristics, PCC dose and time of dose, pre- and post-INR and time of measurement, fresh frozen plasma and vitamin K doses, and patient outcomes were collected. Patients whose pre-PCC International Normalized Ratio (INR) was > 6 h before PCC dose or the pre-post PCC INR was > 12 h were excluded. The primary outcome was achieving an INR ≤ 1.5 post PCC. Secondary outcomes were the change in INR over time, post PCC INR, thromboembolic events (TE), and death during hospital stay. Logistic regression modelled the primary outcome with and without a propensity score adjustment accounting for age, sex, actual body weight, dose, initial INR value, and time between INR measurements. Data are reported as median (IQR) or n (%) with p < 0.05 considered significant. RESULTS: Eighty patients were included (PCC3 = 57, PCC4 = 23). More PCC4 patients achieved goal INR (87.0% vs. 31.6%, odds ratio (OR) = 14.4, 95% CI: 3.80-54.93, p < 0.001). This result remained true after adjusting for possible confounders (AOR = 10.7, 95% CI: 2.17-51.24, p < 0.001). The post-PCC INR was lower in the PCC4 group (1.3 (1.3-1.5) vs. 1.7 (1.5-2.0)). The INR change was greater for PCC4 (2.3 (1.3-3.3) vs. 1.1 (0.6-2.0), p = 0.003). Death during hospital stay (p = 0.52) and TE (p = 1.00) were not significantly different. CONCLUSIONS: PCC4 was associated with a higher achievement of goal INR than PCC3. This relationship was observed in the unadjusted and propensity score adjusted results.

Modelling impact of early vigour on wheat yield in dryland regions.

Early vigour, or faster early leaf area development, has been considered an important trait for rainfed wheat in dryland regions such as Australia. However, early vigour is a genetically complex trait, and results from field experiments have been highly variable. Whether early vigour can lead to improved water use efficiency and crop yields is strongly dependent on climate and management conditions across the entire growing season. Here, we present a modelling framework for simulating the impact of early vigour on wheat growth and yield at eight sites representing the major climate types in Australia. On a typical soil with plant available water capacity (PAWC) of 147 mm, simulated yield increase with early vigour associated with larger seed size was on average 4% higher compared with normal vigour wheat. Early vigour through selection of doubled early leaf sizes could increase yield by 16%. Increase in yield was mainly from increase in biomass and grain number, and was reduced at sites with seasonal rainfall plus initial soil water <300 mm. Opportunities exists for development of early vigour wheat varieties for wetter sites. Soil PAWC could play a significant role in delivering the benefit of early vigour and would require particular attention.

Improving process-based crop models to better capture genotype×environment×management interactions.

In spite of the increasing expectation for process-based crop modelling to capture genotype (G) by environment (E) by management (M) interactions to support breeding selections, it remains a challenge to use current crop models to accurately predict phenotypes from genotypes or from candidate genes. We use wheat as a target crop and the APSIM farming systems model (Holzworth et al., 2014) as an example to analyse the current status of process-based crop models with a major focus on need to improve simulation of specific eco-physiological processes and their linkage to underlying genetic controls. For challenging production environments in Australia, we examine the potential opportunities to capture physiological traits, and to integrate genetic and molecular approaches for future model development and applications. Model improvement will require both reducing the uncertainty in simulating key physiological processes and enhancing the capture of key observable traits and underlying genetic control of key physiological responses to environment. An approach consisting of three interactive stages is outlined to (i) improve modelling of crop physiology, (ii) develop linkage from model parameter to genotypes and further to loci or alleles, and (iii) further link to gene expression pathways. This helps to facilitate the integration of modelling, phenotyping, and functional gene detection and to effectively advance modelling of G×E×M interactions. While gene-based modelling is not always needed to simulate G×E×M, including well-understood gene effects can improve the estimation of genotype effects and prediction of phenotypes. Specific examples are given for enhanced modelling of wheat in the APSIM framework.

Functional popliteal artery entrapment syndrome: A review of diagnostic and management approaches.

Functional popliteal artery entrapment syndrome (FPAES) presents a challenge for clinicians in the field today. The relative rarity of the disease coupled with its affliction primarily in young, athletic individuals makes it a difficult condition to diagnose. Treatment modalities have been limited to surgical intervention, with more novel methods being developed over the last several years. We present a case report and review the diagnostic and management approaches for FPAES, shedding light on proposed future interventions.

A vast, thin plane of corotating dwarf galaxies orbiting the Andromeda galaxy.

Dwarf satellite galaxies are thought to be the remnants of the population of primordial structures that coalesced to form giant galaxies like the Milky Way. It has previously been suspected that dwarf galaxies may not be isotropically distributed around our Galaxy, because several are correlated with streams of H I emission, and may form coplanar groups. These suspicions are supported by recent analyses. It has been claimed that the apparently planar distribution of satellites is not predicted within standard cosmology, and cannot simply represent a memory of past coherent accretion. However, other studies dispute this conclusion. Here we report the existence of a planar subgroup of satellites in the Andromeda galaxy (M 31), comprising about half of the population. The structure is at least 400 kiloparsecs in diameter, but also extremely thin, with a perpendicular scatter of less than 14.1 kiloparsecs. Radial velocity measurements reveal that the satellites in this structure have the same sense of rotation about their host. This shows conclusively that substantial numbers of dwarf satellite galaxies share the same dynamical orbital properties and direction of angular momentum. Intriguingly, the plane we identify is approximately aligned with the pole of the Milky Way's disk and with the vector between the Milky Way and Andromeda.

Meta-Analytic and Economic Approaches for Evaluation of Pesticide Impact on Sclerotinia Stem Rot Control and Soybean Yield in the North Central United States.

As complete host resistance in soybean has not been achieved, Sclerotinia stem rot (SSR) caused by Sclerotinia sclerotiorum continues to be of major economic concern for farmers. Thus, chemical control remains a prevalent disease management strategy. Pesticide evaluations were conducted in Illinois, Iowa, Michigan, Minnesota, New Jersey, and Wisconsin from 2009 to 2016, for a total of 25 site-years (n = 2,057 plot-level data points). These studies were used in network meta-analyses to evaluate the impact of 10 popular pesticide active ingredients, and seven common application timings on SSR control and yield benefit, compared with not treating with a pesticide. Boscalid and picoxystrobin frequently offered the best reductions in disease severity and best yield benefit (P < 0.0001). Pesticide applications (one- or two-spray programs) made during the bloom period provided significant reductions in disease severity index (DIX) (P < 0.0001) and led to significant yield benefits (P = 0.0009). Data from these studies were also used in nonlinear regression analyses to determine the effect of DIX on soybean yield. A three-parameter logistic model was found to best describe soybean yield loss (pseudo-R2 = 0.309). In modern soybean cultivars, yield loss due to SSR does not occur until 20 to 25% DIX, and considerable yield loss (-697 kg ha-1 or -10 bu acre-1) is observed at 68% DIX. Further analyses identified several pesticides and programs that resulted in greater than 60% probability for return on investment under high disease levels.

Lemierre's Syndrome: An Atypical Presentation.

Septic thrombophlebitis is a rare diagnosis in this era of widespread antibiotic usage. The clinical diagnosis requires astute clinical suspicion and evaluation. We describe an asplenic 63-year-old woman who presented to the emergency department with a 24-hour history of a tender, swollen, right neck and upper chest wall. She denied any recent illnesses, but two years before, she was hospitalized and treated for Streptococcus pneumoniae meningitis and endocarditis. An enhanced computed tomography scan demonstrated inflammatory changes around a thrombosed right internal jugular vein, which extended to the brachiocephalic/superior vena cava junction. A retropharyngeal effusion was present, but no pulmonary or oropharyngeal abscess was identified. Lemierre's syndrome, although rare, must be recognized promptly to reduce morbidity and mortality associated with this condition.

Validating Sclerotinia sclerotiorum Apothecial Models to Predict Sclerotinia Stem Rot in Soybean (Glycine max) Fields.

In soybean, Sclerotinia sclerotiorum apothecia are the sources of primary inoculum (ascospores) critical for Sclerotinia stem rot (SSR) development. We recently developed logistic regression models to predict the presence of apothecia in irrigated and nonirrigated soybean fields. In 2017, small-plot trials were established to validate two weather-based models (one for irrigated fields and one for nonirrigated fields) to predict SSR development. Additionally, apothecial scouting and disease monitoring were conducted in 60 commercial fields in three states between 2016 and 2017 to evaluate model accuracy across the growing region. Site-specific air temperature, relative humidity, and wind speed data were obtained through the Integrated Pest Information Platform for Extension and Education (iPiPE) and Dark Sky weather networks. Across all locations, iPiPE-driven model predictions during the soybean flowering period (R1 to R4 growth stages) explained end-of-season disease observations with an accuracy of 81.8% using a probability action threshold of 35%. Dark Sky data, incorporating bias corrections for weather variables, explained end-of-season disease observations with 87.9% accuracy (in 2017 commercial locations in Wisconsin) using a 40% probability threshold. Overall, these validations indicate that these two weather-based apothecial models, using either weather data source, provide disease risk predictions that both reduce unnecessary chemical application and accurately advise applications at critical times.