Recent developments in the use of monoclonal antibodies targeting the type 2 cytokines for severe asthma treatment.

Severe or refractory asthma is seen in approximately 5% of asthmatic subjects who have unsatisfactory symptom control despite adherence to high-dose inhaled glucocorticoid therapies resulting in significant morbidity, reduced quality of life with attendant implications for healthcare costs. Marked heterogeneity in symptoms and at the molecular phenotypic level are hallmarks of asthma resulting in the requirement of specifically targeted treatments to block the key pathways of the disease. Monoclonal antibody (mAb)-based biologics targeted at inhibition of the type 2 cytokines IL-4, IL-5 and IL-13 have become established as effective treatments for severe asthma, with significant clinical benefit seen in carefully selected patient populations that take asthma phenotypes and endotypes into account. The further development of reproducible and straightforward discriminatory biomarkers may aid identification of those patients most likely to benefit from treatment with these interventions.

Genomic selection for target traits in the Australian lentil breeding program.

Genomic selection (GS) uses associations between markers and phenotypes to predict the breeding values of individuals. It can be applied early in the breeding cycle to reduce the cross-to-cross generation interval and thereby increase genetic gain per unit of time. The development of cost-effective, high-throughput genotyping platforms has revolutionized plant breeding programs by enabling the implementation of GS at the scale required to achieve impact. As a result, GS is becoming routine in plant breeding, even in minor crops such as pulses. Here we examined 2,081 breeding lines from Agriculture Victoria's national lentil breeding program for a range of target traits including grain yield, ascochyta blight resistance, botrytis grey mould resistance, salinity and boron stress tolerance, 100-grain weight, seed size index and protein content. A broad range of narrow-sense heritabilities was observed across these traits (0.24-0.66). Genomic prediction models were developed based on 64,781 genome-wide SNPs using Bayesian methodology and genomic estimated breeding values (GEBVs) were calculated. Forward cross-validation was applied to examine the prediction accuracy of GS for these targeted traits. The accuracy of GEBVs was consistently higher (0.34-0.83) than BLUP estimated breeding values (EBVs) (0.22-0.54), indicating a higher expected rate of genetic gain with GS. GS-led parental selection using early generation breeding materials also resulted in higher genetic gain compared to BLUP-based selection performed using later generation breeding lines. Our results show that implementing GS in lentil breeding will fast track the development of high-yielding cultivars with increased resistance to biotic and abiotic stresses, as well as improved seed quality traits.

Identification of agro-physiological traits of lentil that reduce risks of drought.

Ideotype breeding is an essential approach for selection of desired combination of plant traits for testing in crop growth model for potential yield gain in specific environments and management practices. Here we parameterized plant traits for untested lentil cultivars for the APSIM-lentil model in phenology, biomass, and seed yield. We then tested these against independent data and applied the model in an extrapolated analysis (i) to assess the impact of drought on productivity across different rainfall environments; (ii) to identify impactful plant traits and (iii) to design new lentil ideotypes with a combination of desirable traits that mitigate the impact of drought, in the context of various agronomic practices across a wide range of production environments. Desirable phenological and physiological traits related to yield were identified with RUE having the greatest effect on yield followed by HI rate. Leaf size significantly affected seed yield (p< 0.05) more than phenological phases. The physiological traits were integrated into four ideotype designs applied to two baseline cultivars (PBA Hallmark XT and PBA Jumbo2) providing eight ideotypes. We identified a combination of genetic traits that promises a yield advantage of around 10% against our current cultivars PBA Hallmark XT and PBA Jumbo2. Under drought conditions, our ideotypes achieved 5 to 25% yield advantages without stubble and 20 to 40% yield advantages with stubble residues. This shows the importance of genetic screening under realistic production conditions (e.g., stubble retention in particular environments). Such screening is aided by the employment of biophysical models that incorporate both genetic and agronomic variables that focus on successful traits in combination, to reduce the impact of drought in the development of new cultivars for various environments. Stubble retention was found to be a major agronomic contributor to high yield in water-limiting environments and this contribution declined with increasing growing season rainfall. In mid- and high-rainfall environments, the key drivers of yield were time of sowing, physiological traits and soil type. Overall, the agronomic practices, namely, early sowing, residue retention and narrow row spacing deceased the impact of drought when combined with improved physiological traits of the ideotypes based on long term climate data.

Breeding has selected for architectural and photosynthetic traits in lentils.

Genetic progress in seed yield in lentils (Lens culinaris Medik) has increased by 1.1% per year in Australia over the past 27 years. Knowing which plant traits have changed through breeding during this time can give important insights as to how lentil yield has increased. This study aims to identify morphological and physiological traits that were directly or indirectly selected between 1993 and 2020 in the Australian lentil breeding program using 2 years of experimental data. Major changes occurred in plant architecture during this period. Divergent selection has seen the release of varieties that have sprawling to very upright types of canopies. Despite this genetic diversity in recently released varieties, there is an overall tendency of recently released varieties having increased plant height and leaf size with reduced number of branches. Increased light interception was positively correlated with year of release (YOR) and yield, and likely results from indirect selection of yield and taller plant types. There is an indication that recently released varieties have lower CO2 assimilation rate, stomatal conductance and canopy temperature depression (CTD) at high ambient temperatures (~30°C). Understanding lentil physiology will assist in identifying traits to increase yield in a changing climate with extreme weather events.

Combining NDVI and Bacterial Blight Score to Predict Grain Yield in Field Pea.

Field pea is the most commonly grown temperate pulse crop, with close to 15 million tons produced globally in 2020. Varieties improved through breeding are important to ensure ongoing improvements in yield and disease resistance. Genomic selection (GS) is a modern breeding approach that could substantially improve the rate of genetic gain for grain yield, and its deployment depends on the prediction accuracy (PA) that can be achieved. In our study, four yield trials representing breeding lines' advancement stages of the breeding program (S0, S1, S2, and S3) were assessed with grain yield, aerial high-throughput phenotyping (normalized difference vegetation index, NDVI), and bacterial blight disease scores (BBSC). Low-to-moderate broad-sense heritability (0.31-0.71) and narrow-sense heritability (0.13-0.71) were observed, as the estimated additive and non-additive genetic components for the three traits varied with the different models fitted. The genetic correlations among the three traits were high, particularly in the S0-S2 stages. NDVI and BBSC were combined to investigate the PA for grain yield by univariate and multivariate GS models, and multivariate models showed higher PA than univariate models in both cross-validation and forward prediction methods. A 6-50% improvement in PA was achieved when multivariate models were deployed. The highest PA was indicated in the forward prediction scenario when the training population consisted of early generation breeding stages with the multivariate models. Both NDVI and BBSC are commonly used traits that could be measured in the early growth stage; however, our study suggested that NDVI is a more useful trait to predict grain yield with high accuracy in the field pea breeding program, especially in diseased trials, through its incorporation into multivariate models.

Strategies of preserving genetic diversity while maximizing genetic response from implementing genomic selection in pulse breeding programs.

KEY MESSAGE: Genomic selection maximizes genetic gain by recycling parents to germplasm pool earlier and preserves genetic diversity by restricting the number of fixed alleles and the relationship in pulse breeding programs. Using a stochastic computer simulation, we investigated the benefit of optimization strategies in the context of genomic selection (GS) for pulse breeding programs. We simulated GS for moderately complex to highly complex traits such as disease resistance, grain weight and grain yield in multiple environments with a high level of genotype-by-environment interaction for grain yield. GS led to higher genetic gain per unit of time and higher genetic diversity loss than phenotypic selection by shortening the breeding cycle time. The genetic gain obtained from selecting the segregating parents early in the breeding cycle (at F1 or F2 stages) was substantially higher than selecting at later stages even though prediction accuracy was moderate. Increasing the number of F1 intercross (F1i) families and keeping the total number of progeny of F1i families constant, we observed a decrease in genetic gain and increase in genetic diversity, whereas increasing the number of progeny per F1i family while keeping a constant number of F1i families increased the rate of genetic gain and had higher genetic diversity loss per unit of time. Adding 50 F2 family phenotypes to the training population increased the accuracy of genomic breeding values (GEBVs) and genetic gain per year and decreased the rate of genetic diversity loss. Genetic diversity could be preserved by applying a strategy that restricted both the percentage of alleles fixed and the average relationship of the group of selected parents to preserve long-term genetic improvement in the pulse breeding program.

Advances in lentil production through heterosis: Evaluating generations and breeding systems.

Heterosis is defined as increased performance of the F1 hybrid relative to its parents. In the current study, a cohort of populations and parents were created to evaluate and understand heterosis across generations (i.e., F1 to F3) in lentil, a self-pollinated annual diploid (2n = 2× = 14) crop species. Lentil plants were evaluated for heterotic traits in terms of plant height, biomass fresh weight, seed number, yield per plant and 100 grain weight. A total of 47 selected lentil genotypes were cross hybridized to generate 72 F1 hybrids. The F1 hybrids from the top five crosses exhibited between 31%-62% heterosis for seed number with reference to the better parent. The five best performing heterotic crosses were selected with a negative control for evaluation at the subsequent F2 generation and only the tails of the distribution taken forward to be assessed in the F3 generation as a sub selection. Overall, heterosis decreases across the subsequent generations for all traits studied. However, some individual genotypes were identified at the F2 and sub-selected F3 generations with higher levels of heterosis than the best F1 mean value (hybrid mimics). The phenotypic data for the selected F2 and sub selected F3 hybrids were analysed, and the study suggested that 100 grain weight was the biggest driver of yield followed by seed number. A genetic diversity analysis of all the F1 parents failed to correlate genetic distance and divergence among parents with heterotic F1's. Therefore, genetic distance was not a key factor to determine heterosis in lentil. The study highlights the challenges associated with different breeding systems for heterosis (i.e., F1 hybrid-based breeding systems and/or via hybrid mimics) but demonstrates the potential significant gains that could be achieved in lentil productivity.

Australian Lentil Breeding Between 1988 and 2019 Has Delivered Greater Yield Gain Under Stress Than Under High-Yield Conditions.

The contemporary lentil (Lens culinaris ssp. culinaris) industry in Australia started in the late 1980s. Yield in farmers' fields averages 1.2 t ha-1 nationally and has not increased over three decades. Lack of yield progress can be related to a number of non-mutually exclusive reasons: expansion of lentil to low-yielding environments, lack of genetic gain in yield, lack of progress in agronomic practices, and lack of adoption of superior technologies. The aims of this study were to (i) quantify the genetic gain in lentil yield since 1988, (ii) explore the variation in the expression of genetic gain with the environment, and (iii) identify shifts in crop phenotype associated with selection for yield and agronomic adaptation. We grew a historic collection of 19 varieties released between 1988 and 2019 in eight environments resulting from the factorial combination of two sowing dates, two water regimes, and two seasons. Across environments, yield varied 11-fold from 0.2 to 2.2 t ha-1. The rate of genetic gain averaged 20 kg ha-1 year-1 or 1.23% year-1 across environments and was higher in low-yield environments. The yield increase was associated with substantial shifts in phenology. Newer varieties had a shorter time to flowering and pod emergence, and the rate of change in these traits was more pronounced in slow-developing environments (e.g., earlier sowing). Thermal time from sowing to end of flowering and maturity were shorter in newer varieties, and thermal time from pod emergence to maturity was longer in newer varieties; the rate of change in these traits was unrelated to developmental drivers and correlated with environmental mean yield. Genetic gain in yield was associated with increased grain number and increased harvest index. Despite their shorter time to maturity, newer varieties had similar or higher biomass than their older counterparts because crop growth rate during the critical period increased with the year of release. Genotype-dependent yield increased over three decades in low-yield environments, whereas actual farm yield has been stagnant; this suggests an increasing yield gap requiring agronomic solutions. Genetic improvement in high-yield environments requires improved coupling of growth and reproduction.

Performance of an Electronic Decision Support System as a Therapeutic Intervention During a Multicenter PICU Clinical Trial: Heart and Lung Failure-Pediatric Insulin Titration Trial (HALF-PINT).

BACKGROUND: The use of electronic clinical decision support (CDS) systems for pediatric critical care trials is rare. We sought to describe in detail the use of a CDS tool (Children's Hospital Euglycemia for Kids Spreadsheet [CHECKS]), for the management of hyperglycemia during the 32 multicenter Heart And Lung Failure-Pediatric Insulin Titration trial. RESEARCH QUESTION: In critically ill pediatric patients who were treated with CHECKS, how was user compliance associated with outcomes; and what patient and clinician factors might account for the observed differences in CHECKS compliance? STUDY DESIGN AND METHODS: During an observational retrospective study of compliance with a CDS tool used during a prospective randomized controlled trial, we compared patients with high and low CHECKS compliance. We investigated the association between compliance and blood glucose metrics. We describe CHECKS and use a computer interface analysis framework (the user, function, representation, and task analysis framework) to categorize user interactions. We discuss implications for future randomized controlled trials. RESULTS: Over a 4.5-year period, 658 of 698 children were treated with the CHECKS protocol for ≥24 hours with a median of 119 recommendations per patient. Compliance per patient was high (median, 99.5%), with only 30 patients having low compliance (<90%). Patients with low compliance were from 16 of 32 sites, younger (P = .02), and less likely to be on inotropic support (P = .04). They were more likely to be have been assigned randomly to the lower blood glucose target (80% vs 48%; P < .001) and to have spent a shorter time (53% vs 75%; P < .001) at the blood glucose target. Overrides (classified by the user, function, representation, and task analysis framework), were largely (89%) due to the user with patient factors contributing 29% of the time. INTERPRETATION: The use of CHECKS for the Heart And Lung Failure-Pediatric Insulin Titration trial resulted in a highly reproducible and explicit method for the management of hyperglycemia in critically ill children across varied environments. CDS systems represent an important mechanism for conducting explicit complex pediatric critical care trials. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT01565941, registered March 29 2012; https://clinicaltrials.gov/ct2/show/NCT01565941?term=HALF-PINT&draw=2&rank=1.

Pulse Root Ideotype for Water Stress in Temperate Cropping System.

Pulses are a key component of crop production systems in Southern Australia due to their rotational benefits and potential profit margins. However, cultivation in temperate cropping systems such as that of Southern Australia is limited by low soil water availability and subsoil constraints. This limitation of soil water is compounded by the irregular rainfall, resulting in the absence of plant available water at depth. An increase in the productivity of key pulses and expansion into environments and soil types traditionally considered marginal for their growth will require improved use of the limited soil water and adaptation to sub soil constrains. Roots serve as the interface between soil constraints and the whole plant. Changes in root system architecture (RSA) can be utilised as an adaptive strategy in achieving yield potential under limited rainfall, heterogenous distribution of resources and other soil-based constraints. The existing literature has identified a "'Steep, Deep and Cheap" root ideotype as a preferred RSA. However, this idiotype is not efficient in a temperate system where plant available water is limited at depth. In addition, this root ideotype and other root architectural studies have focused on cereal crops, which have different structures and growth patterns to pulses due to their monocotyledonous nature and determinant growth habit. The paucity of pulse-specific root architectural studies warrants further investigations into pulse RSA, which should be combined with an examination of the existing variability of known genetic traits so as to develop strategies to alleviate production constraints through either tolerance or avoidance mechanisms. This review proposes a new model of root system architecture of "Wide, Shallow and Fine" roots based on pulse roots in temperate cropping systems. The proposed ideotype has, in addition to other root traits, a root density concentrated in the upper soil layers to capture in-season rainfall before it is lost due to evaporation. The review highlights the potential to achieve this in key pulse crops including chickpea, lentil, faba bean, field pea and lupin. Where possible, comparisons to determinate crops such as cereals have also been made. The review identifies the key root traits that have shown a degree of adaptation via tolerance or avoidance to water stress and documents the current known variability that exists in and amongst pulse crops setting priorities for future research.

Molecular Biology of Eosinophils: Introduction.

The eosinophil is an enigmatic cell with a continuing ability to fascinate. A considerable history of research endeavor on eosinophil biology stretches from the present time back to the nineteenth century. Perhaps one of the most fascinating aspects of the eosinophil is how accumulating knowledge has changed the perception of its function from passive bystander, modulator of inflammation, to potent effector cell loaded with histotoxic substances through to more recent recognition that it can act as both a positive and negative regulator of complex events in both innate and adaptive immunity. This book consists of chapters written by experts in the field of eosinophil biology that provide comprehensive clearly written protocols for techniques designed to underpin research into the function of the eosinophil in health and disease.

Anti-IL-5 monoclonal antibodies for the treatment of asthma: an update.

INTRODUCTION: Asthma exhibits marked heterogeneity in symptoms with severe or refractory asthma representing a clear area of unmet medical need. These patients require more specifically targeted treatments with monoclonal antibody-based biologics targeted at inhibition of the type 2 cytokines IL-4, IL-5 and IL-13 having considerable potential as effective treatments for severe asthma. For the most part, anti-cytokine-based biologic therapies are more likely to give significant clinical benefit in carefully selected patient populations that take asthma phenotypes and endotypes into account. AREAS COVERED: This review is based on recent English-language original articles in Pub Med or MedLine that reported significant clinical findings on the current status, therapeutic potential and safety of the anti-IL-5 biologics mepolizumab, reslizumab and benralizumab in the treatment of severe refractory asthma. EXPERT OPINION: Anti-IL-5 treatment appears effective in patients with eosinophilic asthma through exacerbation prevention with accumulating evidence of glucocorticoid-sparing effects with an acceptable safety profile for these biologics.

Amount and Type of Dietary Fat, Postprandial Glycemia, and Insulin Requirements in Type 1 Diabetes: A Randomized Within-Subject Trial.

OBJECTIVE: The American Diabetes Association recommends individuals with type 1 diabetes (T1D) adjust insulin for dietary fat; however, optimal adjustments are not known. This study aimed to determine 1) the relationship between the amount and type of dietary fat and glycemia and 2) the optimal insulin adjustments for dietary fat. RESEARCH DESIGN AND METHODS: Adults with T1D using insulin pump therapy attended the research clinic on 9-12 occasions. On the first six visits, participants consumed meals containing 45 g carbohydrate with 0 g, 20 g, 40 g, or 60 g fat and either saturated, monounsaturated, or polyunsaturated fat. Insulin was dosed using individual insulin/carbohydrate ratio as a dual-wave 50/50% over 2 h. On subsequent visits, participants repeated the 20-60-g fat meals with the insulin dose estimated using a model predictive bolus, up to twice per meal, until glycemic control was achieved. RESULTS: With the same insulin dose, increasing the amount of fat resulted in a significant dose-dependent reduction in incremental area under the curve for glucose (iAUCglucose) in the early postprandial period (0-2 h; P = 0.008) and increase in iAUCglucose in the late postprandial period (2-5 h; P = 0.004). The type of fat made no significant difference to the 5-h iAUCglucose. To achieve glycemic control, on average participants required dual-wave insulin bolus: for 20 g fat, +6% insulin, 74/26% over 73 min; 40 g fat, +6% insulin, 63/37% over 75 min; and 60 g fat, +21% insulin, 49/51% over 105 min. CONCLUSIONS: This study provides clinical guidance for mealtime insulin dosing recommendations for dietary fat in T1D.

The crystal and molecular structures of three copper-containing complexes and their activities in mimicking galactose oxidase.

The structures of three copper-containing complexes, namely (benzoato-κ2O,O')[(E)-2-({[2-(diethylamino)ethyl]imino}methyl)phenolato-κ3N,N',O]copper(II) dihydrate, [Cu(C7H5O2)(C13H19N2O)]·2H2O, 1, [(E)-2-({[2-(diethylamino)ethyl]imino}methyl)phenolato-κ3N,N',O](2-phenylacetato-κ2O,O')copper(II), [Cu(C8H7O2)(C13H19N2O)], 2, and bis[µ-(E)-2-({[3-(diethylamino)propyl]imino}methyl)phenolato]-κ4N,N',O:O;κ4O:N,N',O-(µ-2-methylbenzoato-κ2O:O')copper(II) perchlorate, [Cu2(C8H7O2)(C12H17N2O)2]ClO4, 3, have been reported and all have been tested for their activity in the oxidation of D-galactose. The results suggest that, unlike the enzyme galactose oxidase, due to the precipitation of Cu2O, this reaction is not catalytic as would have been expected. The structures of 1 and 2 are monomeric, while 3 consists of a dimeric cation and a perchlorate anion [which is disordered over two orientations, with occupancies of 0.64 (4) and 0.36 (4)]. In all three structures, the central Cu atom is five-coordinated in a distorted square-pyramidal arrangment (τ parameter of 0.0932 for 1, 0.0888 for 2, and 0.142 and 0.248 for the two Cu centers in 3). In each species, the environment about the Cu atom is such that the vacant sixth position is open, with very little steric crowding.

Continuous Glucose Monitoring Linked to an Artificial Intelligence Risk Index: Early Footprints of Intraventricular Hemorrhage in Preterm Neonates.

OBJECTIVE: To develop and validate a new risk score for intraventricular hemorrhage (IVH) in preterm neonates based on continuous glucose monitoring (CGM). STUDY DESIGN: We retrospectively analyzed CGM traces obtained from 50 very preterm neonates, grouped into two sub-cohorts started on CGM within 12 and 48 h of birth, respectively. A CGM linked to an Artificial Intelligence Risk (CLAIR) index was developed to quantify glucose variability during the first 72 h of life in neonates with and without IVH. Brain-US was performed at least twice a day for the first 5 days of birth. An integrated remote monitoring platform was developed to capture major clinical events in real time and gather data for the risk index. The new score performance was further compared with other measures of glucose variability (coefficient of variation [CV] and standard deviation [SD]) and with a clinical risk index for babies II (CRIB-II) as a predictor of IVH event. The two cohorts were analyzed separately for internal validation of the method. RESULTS: The primary cohort consisted of 26 neonates (gestational age 30 [28, 31] weeks; BW1275 g[1090, 1750]). Controls (n = 23) exhibited higher CLAIR index than cases (P = 0.004). A cut-off of 0.69 for the new CLAIR index allowed a 100% sensitivity and an 83% specificity for IVH prediction. The CLAIR index was the sole significant predictor for IVH (P = 0.003) when compared with clinical variables, CV, SD, and CRIB-II. In a subgroup analysis in very low-birth-weight infants, the CLAIR index was the sole variable significantly associated with IVH (P = 0.009). Analysis on the secondary cohort (five cases and 16 controls) confirmed a higher CLAIR index in the controls (P = 0.008), in the absence of a difference for CV, SD, and CRIB-II between the two groups. CONCLUSION: CGM, combined with the AI-algorithm, provides a high-sensitivity index for risk detection of IVH that reflects the glycemic impairment preceding IVH.

Short-Term Adverse Outcomes Associated With Hypoglycemia in Critically Ill Children.

OBJECTIVES: Previous studies report worse short-term outcomes with hypoglycemia in critically ill children. These studies relied on intermittent blood glucose measurements, which may have introduced detection bias. We analyzed data from the Heart And Lung Failure-Pediatric INsulin Titration trial to determine the association of hypoglycemia with adverse short-term outcomes in critically ill children. DESIGN: Nested case-control study. SETTING: Thirty-five PICUs. A computerized algorithm that guided the timing of blood glucose measurements and titration of insulin infusion, continuous glucose monitors, and standardized glucose infusion rates were used to minimize hypoglycemia. PATIENTS: Nondiabetic children with cardiovascular and/or respiratory failure and hyperglycemia. Cases were children with any hypoglycemia (blood glucose < 60 mg/dL), whereas controls were children without hypoglycemia. Each case was matched with up to four unique controls according to age group, study day, and severity of illness. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: A total of 112 (16.0%) of 698 children who received the Heart And Lung Failure-Pediatric INsulin Titration protocol developed hypoglycemia, including 25 (3.6%) who developed severe hypoglycemia (blood glucose < 40 mg/dL). Of these, 110 cases were matched to 427 controls. Hypoglycemia was associated with fewer ICU-free days (median, 15.3 vs 20.2 d; p = 0.04) and fewer hospital-free days (0 vs 7 d; p = 0.01) through day 28. Ventilator-free days through day 28 and mortality at 28 and 90 days did not differ between groups. More children with insulin-induced versus noninsulin-induced hypoglycemia had zero ICU-free days (35.8% vs 20.9%; p = 0.008). Outcomes did not differ between children with severe versus nonsevere hypoglycemia or those with recurrent versus isolated hypoglycemia. CONCLUSIONS: When a computerized algorithm, continuous glucose monitors and standardized glucose infusion rates were used to manage hyperglycemia in critically ill children with cardiovascular and/or respiratory failure, severe hypoglycemia (blood glucose < 40 mg/dL) was uncommon, but any hypoglycemia (blood glucose < 60 mg/dL) remained common and was associated with worse short-term outcomes.

Automated phenotyping for early vigour of field pea seedlings in controlled environment by colour imaging technology.

Early vigour of seedlings is a beneficial trait of field pea (Pisum sativum L.) that contributes to weed control, water use efficiency and is likely to contribute to yield under certain environments. Although breeding is considered the most effective approach to improve early vigour of field pea, the absence of a robust and high-throughput phenotyping tool to dissect this complex trait is currently a major obstacle of genetic improvement programs to address this issue. To develop this tool, separate trials on 44 genetically diverse field pea genotypes were conducted in the automated plant phenotyping platform of Plant Phenomics Victoria, Horsham and in the field, respectively. High correlation between estimated plant parameters derived from the automated phenotyping platform and important early vigour traits such as shoot biomass, leaf area and plant height indicated that the derived plant parameters can be used to predict vigour traits in field pea seedlings. Plant growth analysis demonstrated that the "broken-stick" model fitted well with the growth pattern of all field pea genotypes and can be used to determine the linear growth phase. Further analysis suggested that the estimated plant parameters collected at the linear growth phase can effectively differentiate early vigour across field pea genotypes. High correlation between normalised difference vegetation indices captured from the field trial and estimated shoot biomass and top-view area confirmed the consistent performance of early vigour field pea genotypes under controlled and field environments. Overall, our results demonstrated that this robust screening tool is highly applicable and will enable breeding programs to rapidly identify early vigour traits and utilise germplasm to contribute to the genetic improvement of field peas.

Recent developments in the use of biologics targeting IL-5, IL-4, or IL-13 in severe refractory asthma.

INTRODUCTION: Severe or refractory asthma is seen in approximately 5% of asthmatic subjects who have unsatisfactory symptom control despite adherence to high-dose inhaled glucocorticoid therapies resulting in significant morbidity, reduced quality of life and health-care cost implications. Asthma exhibits marked heterogeneity both clinically and at the molecular phenotypic level requiring specifically targeted treatments to block the key pathways of the disease. Monoclonal antibody-based biologics targeted at inhibition of the type 2 cytokines IL-4, IL-5, and IL-13 have considerable potential as effective treatments for severe asthma. Areas covered: This review is based on recent English-language original articles in PubMed or Medline that reported significant clinical findings on the current status, therapeutic potential, and safety of biologics targeted at IL-4, IL-5, and IL-13 in the treatment of asthma together with the potential utility of simple reproducible non-invasive biomarkers to guide the effective use of biologic-based therapy that do not require direct sampling of the airways Expert commentary: The further development of reproducible and straightforward discriminatory non-invasive biomarkers may aid identification of those patients most likely to benefit from treatment with these interventions.

Adjusting Insulin Delivery to Activity (AIDA) clinical trial: Effects of activity-based insulin profiles on glucose control in children with type 1 diabetes.

BACKGROUND: Increased daytime activity in children with type I diabetes mellitus (T1DM) is associated with increased risk of hypoglycemia. OBJECTIVE: To determine whether an automated weekly review of accelerometer, continuous glucose monitoring (CGM), and insulin pump data, could be used to identify children with increased risk of nighttime hypoglycemia and preemptively adjust the nighttime basal insulin profile according to daytime activity. RESEARCH AND DESIGN METHODS: Clinical trial of children with T1DM on insulin pump and CGM therapy. Subjects at risk of nighttime hypoglycemia were identified from regression analysis of daytime step count vs nighttime nadir glucose. If the regression slope was significantly different from zero (P < 0.05) subjects were managed with different algorithm derived nighttime basal insulin profiles following high and low activity days. RESULTS: Twenty children (median age: 12; range: 7-17 years) were enrolled. Regression slopes were significant in 10 children. In these children, baseline nighttime nadir glucose level was lower following high activity days (120 [110-139] vs 152 [130-162] mg/dL, P = 0.004). Use of activity-based nighttime basal profiles produced similar nighttime nadir glucose levels following high and low activity days (136 [123-175] vs 140 [108-180] mg/dL, P = 0.73) with fewer nighttime interventions to correct hypoglycemia (0 [0-0.16] vs 0.15 [0.13-0.22] per night, P = 0.008). CONCLUSION: Children with lower nighttime glucose levels following high daytime activity can be identified using step count data obtained from readily available accelerometers and the nighttime glucose control improved using different activity-based basal profiles.

Autoreactive T effector memory differentiation mirrors ß cell function in type 1 diabetes.

In type 1 diabetes, cytotoxic CD8+ T cells with specificity for ß cell autoantigens are found in the pancreatic islets, where they are implicated in the destruction of insulin-secreting ß cells. In contrast, the disease relevance of ß cell-reactive CD8+ T cells that are detectable in the circulation, and their relationship to ß cell function, are not known. Here, we tracked multiple, circulating ß cell-reactive CD8+ T cell subsets and measured ß cell function longitudinally for 2 years, starting immediately after diagnosis of type 1 diabetes. We found that change in ß cell-specific effector memory CD8+ T cells expressing CD57 was positively correlated with C-peptide change in subjects below 12 years of age. Autoreactive CD57+ effector memory CD8+ T cells bore the signature of enhanced effector function (higher expression of granzyme B, killer-specific protein of 37 kDa, and CD16, and reduced expression of CD28) compared with their CD57- counterparts, and network association modeling indicated that the dynamics of ß cell-reactive CD57+ effector memory CD8+ T cell subsets were strongly linked. Thus, coordinated changes in circulating ß cell-specific CD8+ T cells within the CD57+ effector memory subset calibrate to functional insulin reserve in type 1 diabetes, providing a tool for immune monitoring and a mechanism-based target for immunotherapy.