Optimal crop emergence is an important trait in crop breeding for genotypic screening and for achieving potential growth and yield. Emergence is conventionally quantified manually by counting the sub-sections of field plots or scoring; these are less reliable, laborious and inefficient. Remote sensing technology is being increasingly used for high-throughput estimation of agronomic traits in field crops. This study developed a method for estimating wheat seedlings using multispectral images captured from an unmanned aerial vehicle. A machine learning regression (MLR) analysis was used by combining spectral and morphological information extracted from the multispectral images. The approach was tested on diverse wheat genotypes varying in seedling emergence. In this study, three supervised MLR models including regression trees, support vector regression and Gaussian process regression (GPR) were evaluated for estimating wheat seedling emergence. The GPR model was the most effective compared to the other methods, with R2 = 0.86, RMSE = 4.07 and MAE = 3.21 when correlated to the manual seedling count. In addition, imagery data collected at multiple flight altitudes and different wheat growth stages suggested that 10 m altitude and 20 days after sowing were desirable for optimal spatial resolution and image analysis. The method is deployable on larger field trials and other crops for effective and reliable seedling emergence estimates.

Objectives: Although co-expression of CD38 and HLA-DR reflects T-cell activation during viral infections, high and prolonged CD38+HLA-DR+ expression is associated with severe disease. To date, the mechanism underpinning expression of CD38+HLA-DR+ is poorly understood. Methods: We used mouse models of influenza A/H9N2, A/H7N9 and A/H3N2 infection to investigate mechanisms underpinning CD38+MHC-II+ phenotype on CD8+ T cells. To further understand MHC-II trogocytosis on murine CD8+ T cells as well as the significance behind the scenario, we used adoptively transferred transgenic OT-I CD8+ T cells and A/H3N2-SIINKEKL infection. Results: Analysis of influenza-specific immunodominant DbNP366 +CD8+ T-cell responses showed that CD38+MHC-II+ co-expression was detected on both virus-specific and bystander CD8+ T cells, with increased numbers of both CD38+MHC-II+CD8+ T-cell populations observed in immune organs including the site of infection during severe viral challenge. OT-I cells adoptively transferred into MHC-II-/- mice had no MHC-II after infection, suggesting that MHC-II was acquired via trogocytosis. The detection of CD19 on CD38+MHC-II+ OT-I cells supports the proposition that MHC-II was acquired by trogocytosis sourced from B cells. Co-expression of CD38+MHC-II+ on CD8+ T cells was needed for optimal recall following secondary infection. Conclusions: Overall, our study demonstrates that both virus-specific and bystander CD38+MHC-II+ CD8+ T cells are recruited to the site of infection during severe disease, and that MHC-II presence occurs via trogocytosis from antigen-presenting cells. Our findings highlight the importance of the CD38+MHC-II+ phenotype for CD8+ T-cell recall.

We describe severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-specific immune responses in a patient with lymphoma and recent programmed death 1 (PD-1) inhibitor therapy with late onset of severe coronavirus disease 2019 disease and prolonged SARS-CoV-2 replication, in comparison to age-matched and immunocompromised controls. High levels of HLA-DR+/CD38+ activation, interleukin 6, and interleukin 18 in the absence of B cells and PD-1 expression was observed. SARS-CoV-2-specific antibody responses were absent and SARS-CoV-2-specific T cells were minimally detected. This case highlights challenges in managing immunocompromised hosts who may fail to mount effective virus-specific immune responses.

The host response to SARS-CoV-2 infection provide insights into both viral pathogenesis and patient management. The host-encoded microRNA (miRNA) response to SARS-CoV-2 infection, however, remains poorly defined. Here we profiled circulating miRNAs from ten COVID-19 patients sampled longitudinally and ten age and gender matched healthy donors. We observed 55 miRNAs that were altered in COVID-19 patients during early-stage disease, with the inflammatory miR-31-5p the most strongly upregulated. Supervised machine learning analysis revealed that a three-miRNA signature (miR-423-5p, miR-23a-3p and miR-195-5p) independently classified COVID-19 cases with an accuracy of 99.9%. In a ferret COVID-19 model, the three-miRNA signature again detected SARS-CoV-2 infection with 99.7% accuracy, and distinguished SARS-CoV-2 infection from influenza A (H1N1) infection and healthy controls with 95% accuracy. Distinct miRNA profiles were also observed in COVID-19 patients requiring oxygenation. This study demonstrates that SARS-CoV-2 infection induces a robust host miRNA response that could improve COVID-19 detection and patient management.

Drought is one of the most severe and unpredictable abiotic stresses, occurring at any growth stage and affecting crop yields worldwide. Therefore, it is essential to develop drought tolerant varieties to ensure sustainable crop production in an ever-changing climate. High-throughput digital phenotyping technologies in tandem with robust screening methods enable precise and faster selection of genotypes for breeding. To investigate the use of digital imaging to reliably phenotype for drought tolerance, a genetically diverse safflower population was screened under different drought stresses at Agriculture Victoria's high-throughput, automated phenotyping platform, Plant Phenomics Victoria, Horsham. In the first experiment, four treatments, control (90% field capacity; FC), 40% FC at initial branching, 40% FC at flowering and 50% FC at initial branching and flowering, were applied to assess the performance of four safflower genotypes. Based on these results, drought stress using 50% FC at initial branching and flowering stages was chosen to further screen 200 diverse safflower genotypes. Measured plant traits and dry biomass showed high correlations with derived digital traits including estimated shoot biomass, convex hull area, caliper length and minimum area rectangle, indicating the viability of using digital traits as proxy measures for plant growth. Estimated shoot biomass showed close association having moderately high correlation with drought indices yield index, stress tolerance index, geometric mean productivity, and mean productivity. Diverse genotypes were classified into four clusters of drought tolerance based on their performance (seed yield and digitally estimated shoot biomass) under stress. Overall, results show that rapid and precise image-based, high-throughput phenotyping in controlled environments can be used to effectively differentiate response to drought stress in a large numbers of safflower genotypes.

Salinity is a major contributing factor to the degradation of arable land, and reductions in crop growth and yield. To overcome these limitations, the breeding of crop varieties with improved salt tolerance is needed. This requires effective and high-throughput phenotyping to optimize germplasm enhancement. Safflower (Carthamus tinctorius L.), is an underappreciated but highly versatile oilseed crop, capable of growing in saline and arid environments. To develop an effective and rapid phenotyping protocol to differentiate salt responses in safflower genotypes, experiments were conducted in the automated imaging facility at Plant Phenomics Victoria, Horsham, focussing on digital phenotyping at early vegetative growth. The initial experiment, at 0, 125, 250, and 350 mM sodium chloride (NaCl), showed that 250 mM NaCl was optimum to differentiate salt sensitive and tolerant genotypes. Phenotyping of a diverse set of 200 safflower genotypes using the developed protocol defined four classes of salt tolerance or sensitivity, based on biomass and ion accumulation. Salt tolerance in safflower was dependent on the exclusion of Na+ from shoot tissue and the maintenance of K+ uptake. Salinity response identified in glasshouse experiments showed some consistency with the performance of representatively selected genotypes tested under sodic field conditions. Overall, our results suggest that digital phenotyping can be an effective high-throughput approach in identifying candidate genotypes for salt tolerance in safflower.

The innate immune system is our first line of defense against viral pathogens. Host cell pattern recognition receptors sense viral components and initiate immune signaling cascades that result in the production of an array of cytokines to combat infection. Retinoic acid-inducible gene-I (RIG-I) is a pattern recognition receptor that recognizes viral RNA and, when activated, results in the production of type I and III interferons (IFNs) and the upregulation of IFN-stimulated genes. Ubiquitination of RIG-I by the E3 ligases tripartite motif-containing 25 (TRIM25) and Riplet is thought to be requisite for RIG-I activation; however, recent studies have questioned the relative importance of these two enzymes for RIG-I signaling. In this study, we show that deletion of Trim25 does not affect the IFN response to either influenza A virus (IAV), influenza B virus, Sendai virus or several RIG-I agonists. This is in contrast to deletion of either Rig-i or Riplet, which completely abrogated RIG-I-dependent IFN responses. This was consistent in both mouse and human cell lines, as well as in normal human bronchial cells. With most of the current TRIM25 literature based on exogenous expression, these findings provide critical evidence that Riplet, and not TRIM25, is required endogenously for the ubiquitination of RIG-I. Despite this, loss of TRIM25 results in greater susceptibility to IAV infection in vivo, suggesting that it may have an alternative role in host antiviral defense. This study refines our understanding of RIG-I signaling in viral infections and will inform future studies in the field.

The present study evaluated the effects of energetic undernutrition on liquid and solid digesta passage and on nutrient digestibility as well as their interdependencies. Using a 4 x 4 Latin square design, 12 growing Boran steers (183 ± 15.2 kg live weight) were allocated to four levels of metabolizable energy (ME) supply fixed at 100, 80, 60 and 40% of individual maintenance energy requirements (MER) during four experimental periods. Each period comprised three weeks of adaptation, two weeks of data collection and two weeks of recovery. Diets MER80, MER60 and MER40 only consisted of Rhodes grass hay (RGH), whereas diet MER100 contained (as fed) 83% RGH, 8% cotton seed meal and 9% sugarcane molasses. Feed intake differed between treatments (p < .001) and ranged from 40 ± 0.6 g dry matter (DM) per kg of metabolic weight (kg0.75 ) in MER40 to 81 ± 1.3 g DM in MER100. Digestibility of neutral and acid detergent fibre (NDF, ADF) was highest at MER80, whereas rumen retention time of liquid and solid digesta was longest at MER40. The correlation of rumen retention time of liquid and solid digesta with the digestibility of proximate diet components was weak but positive, whereas the correlation of liquid and solid rumen retention time with quantitative feed and nutrient intake was strong (p < .01) and negative. Our results suggest that tropical cattle are able to buffer a moderate energy deficit by prolonging rumen retention time of digesta and hence improve diet digestibility. Conversely, a severe energy deficit cannot be buffered by digestive adaptation mechanisms and will inevitably lead to productivity losses.

This field observational study describes the seasonal pattern of small lungworm infections under different grazing managements from August 2018 to March 2019. Live weight, lungworm and gastrointestinal nematode infection, as well as pasture type grazed and snail density, were measured at 5 farm visits. Across all visits and mobs, about one quarter to one half of sheep were positive for small lungworm, although prevalence was as low as 0% and as high as 78%. The density of the intermediate host molluscs was greater than 1600 snails/m2 in irrigated perennial lucerne pasture when it was grazed ('Pasture A'), but was low (<300) in non-irrigated perennial pasture ('Pasture B') and non-irrigated forage crop ('Pasture C'). Overall, non-infected lambs had a similar live weight compared with the small lungworm infected lambs (mean difference -0.6 kg; 95% CI -1.6 to 0.2; P = 0.1). The odds ratio of small lungworm infection associated with a twofold increase in worm egg count was 1.7 (95% CI 1.1 to 2.7; P = 0.02). Rather than a distinct seasonal pattern of infection, we found that small lungworm can occur throughout the year, with prevalence most influenced by pasture type (irrigated vs dryland), grazing management and the population density of the intermediate hosts. Importantly, this study suggested that small lungworm infection did not reduce lamb live weights. It reinforced that to improve sheep productivity, well-established determinants of production, such as correct grazing management to optimise pasture quality and strategies to reduce infections with gastrointestinal nematodes, should be the priority of farm managers.