Profiling of Fusarium head blight resistance QTL haplotypes through molecular markers, genotyping-by-sequencing, and machine learning.

KEY MESSAGE: Marker-assisted selection is important for cultivar development. We propose a system where a training population genotyped for QTL and genome-wide markers may predict QTL haplotypes in early development germplasm. Breeders screen germplasm with molecular markers to identify and select individuals that have desirable haplotypes. The objective of this research was to investigate whether QTL haplotypes can be accurately predicted using SNPs derived by genotyping-by-sequencing (GBS). In the SunGrains program during 2020 (SG20) and 2021 (SG21), 1,536 and 2,352 lines submitted for GBS were genotyped with markers linked to the Fusarium head blight QTL: Qfhb.nc-1A, Qfhb.vt-1B, Fhb1, and Qfhb.nc-4A. In parallel, data were compiled from the 2011-2020 Southern Uniform Winter Wheat Scab Nursery (SUWWSN), which had been screened for the same QTL, sequenced via GBS, and phenotyped for: visual Fusarium severity rating (SEV), percent Fusarium damaged kernels (FDK), deoxynivalenol content (DON), plant height, and heading date. Three machine learning models were evaluated: random forest, k-nearest neighbors, and gradient boosting machine. Data were randomly partitioned into training-testing splits. The QTL haplotype and 100 most correlated GBS SNPs were used for training and tuning of each model. Trained machine learning models were used to predict QTL haplotypes in the testing partition of SG20, SG21, and the total SUWWSN. Mean disease ratings for the observed and predicted QTL haplotypes were compared in the SUWWSN. For all models trained using the SG20 and SG21, the observed Fhb1 haplotype estimated group means for SEV, FDK, DON, plant height, and heading date in the SUWWSN were not significantly different from any of the predicted Fhb1 calls. This indicated that machine learning may be utilized in breeding programs to accurately predict QTL haplotypes in earlier generations.

Thrombotic and haemorrhagic complications in critically ill patients with COVID-19: a multicentre observational study.

BACKGROUND: Optimal prophylactic and therapeutic management of thromboembolic disease in patients with COVID-19 remains a major challenge for clinicians. The aim of this study was to define the incidence of thrombotic and haemorrhagic complications in critically ill patients with COVID-19. In addition, we sought to characterise coagulation profiles using thromboelastography and explore possible biological differences between patients with and without thrombotic complications. METHODS: We conducted a multicentre retrospective observational study evaluating all the COVID-19 patients received in four intensive care units (ICUs) of four tertiary hospitals in the UK between March 15, 2020, and May 05, 2020. Clinical characteristics, laboratory data, thromboelastography profiles and clinical outcome data were evaluated between patients with and without thrombotic complications. RESULTS: A total of 187 patients were included. Their median (interquartile (IQR)) age was 57 (49-64) years and 124 (66.3%) patients were male. Eighty-one (43.3%) patients experienced one or more clinically relevant thrombotic complications, which were mainly pulmonary emboli (n = 42 (22.5%)). Arterial embolic complications were reported in 25 (13.3%) patients. ICU length of stay was longer in patients with thrombotic complications when compared with those without. Fifteen (8.0%) patients experienced haemorrhagic complications, of which nine (4.8%) were classified as major bleeding. Thromboelastography demonstrated a hypercoagulable profile in patients tested but lacked discriminatory value between those with and without thrombotic complications. Patients who experienced thrombotic complications had higher D-dimer, ferritin, troponin and white cell count levels at ICU admission compared with those that did not. CONCLUSION: Critically ill patients with COVID-19 experience high rates of venous and arterial thrombotic complications. The rates of bleeding may be higher than previously reported and re-iterate the need for randomised trials to better understand the risk-benefit ratio of different anticoagulation strategies.

Mechanistic insights into cardiovascular protection for omega-3 fatty acids and their bioactive lipid metabolites.

Patients with well-controlled low-density lipoprotein cholesterol levels, but persistent high triglycerides, remain at increased risk for cardiovascular events as evidenced by multiple genetic and epidemiologic studies, as well as recent clinical outcome trials. While many trials of low-dose ω3-polyunsaturated fatty acids (ω3-PUFAs), eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA) have shown mixed results to reduce cardiovascular events, recent trials with high-dose ω3-PUFAs have reignited interest in ω3-PUFAs, particularly EPA, in cardiovascular disease (CVD). REDUCE-IT demonstrated that high-dose EPA (4 g/day icosapent-ethyl) reduced a composite of clinical events by 25% in statin-treated patients with established CVD or diabetes and other cardiovascular risk factors. Outcome trials in similar statin-treated patients using DHA-containing high-dose ω3 formulations have not yet shown the benefits of EPA alone. However, there are data to show that high-dose ω3-PUFAs in patients with acute myocardial infarction had reduced left ventricular remodelling, non-infarct myocardial fibrosis, and systemic inflammation. ω3-polyunsaturated fatty acids, along with their metabolites, such as oxylipins and other lipid mediators, have complex effects on the cardiovascular system. Together they target free fatty acid receptors and peroxisome proliferator-activated receptors in various tissues to modulate inflammation and lipid metabolism. Here, we review these multifactorial mechanisms of ω3-PUFAs in view of recent clinical findings. These findings indicate physico-chemical and biological diversity among ω3-PUFAs that influence tissue distributions as well as disparate effects on membrane organization, rates of lipid oxidation, as well as various receptor-mediated signal transduction pathways and effects on gene expression.

Training population selection and use of fixed effects to optimize genomic predictions in a historical USA winter wheat panel.

KEY MESSAGE: The optimization of training populations and the use of diagnostic markers as fixed effects increase the predictive ability of genomic prediction models in a cooperative wheat breeding panel. Plant breeding programs often have access to a large amount of historical data that is highly unbalanced, particularly across years. This study examined approaches to utilize these data sets as training populations to integrate genomic selection into existing pipelines. We used cross-validation to evaluate predictive ability in an unbalanced data set of 467 winter wheat (Triticum aestivum L.) genotypes evaluated in the Gulf Atlantic Wheat Nursery from 2008 to 2016. We evaluated the impact of different training population sizes and training population selection methods (Random, Clustering, PEVmean and PEVmean1) on predictive ability. We also evaluated inclusion of markers associated with major genes as fixed effects in prediction models for heading date, plant height, and resistance to powdery mildew (caused by Blumeria graminis f. sp. tritici). Increases in predictive ability as the size of the training population increased were more evident for Random and Clustering training population selection methods than for PEVmean and PEVmean1. The selection methods based on minimization of the prediction error variance (PEV) outperformed the Random and Clustering methods across all the population sizes. Major genes added as fixed effects always improved model predictive ability, with the greatest gains coming from combinations of multiple genes. Maximum predictabilities among all prediction methods were 0.64 for grain yield, 0.56 for test weight, 0.71 for heading date, 0.73 for plant height, and 0.60 for powdery mildew resistance. Our results demonstrate the utility of combining unbalanced phenotypic records with genome-wide SNP marker data for predicting the performance of untested genotypes.

The prognostic significance of incomplete revascularization and untreated coronary anatomy following percutaneous coronary intervention: An analysis of 6,755 patients with multivessel disease.

BACKGROUND: More than half of the patients undergoing percutaneous coronary intervention (PCI) have multivessel disease. Whether complete revascularization impacts long-term mortality or whether selected patients or those with specific coronary anatomy benefit from complete revascularization is unclear. METHODS: A total of 14,452 patients underwent PCI between 2004 and 2015 at Harefield Hospital, UK. Of these, 7,076 patients had multivessel disease. We excluded 321 patients with left main-stem stenosis ≥50%, with 6,755 patients included in the analysis (936 patients had complete revascularization). RESULTS: The unadjusted 3-year mortality rates were lower with complete revascularization (10.8% vs 13.1%, P = 0.047). However, multivariable-adjusted analyses indicated that complete revascularization was not independently associated with mortality (HR = 1.01, 95% CI: 0.78-1.31, P = 0.939). These findings were unchanged when addressing measured confounding using propensity-matched analyses (HR = 1.16, 95% CI: 0.81-1.65, P = 0.417) and inverse probability treatment weighted analyses (HR = 1.01, 95% CI: 0.77-1.33, P = 0.950); and unmeasured confounding using instrumental variable analyses (Δ = 0.9%, 95% CI: -2.5%, 4.3%, P = 0.958). There was no association with mortality and untreated LAD disease (HR = 0.92, 95% CI: 0.72-1.17, P = 0.482) and LCx disease (HR = 0.90, 95% CI: 0.74-1.10, P = 0.999). However, untreated proximal LAD disease (HR = 1.23, 95% CI: 1.06-1.51, P = 0.045) and RCA disease (HR = 1.36, 95% CI: 1.08-1.65, P = 0.007) was associated with increased mortality, particularly in patients with ST-elevation acute coronary syndrome (STEACS). CONCLUSIONS: In this study of unselected patients undergoing PCI, complete revascularization did not confer a mortality benefit. However, the presence of untreated proximal LAD and RCA disease was prognostic in patients with STEACS. Thus, complete revascularization may be considered in select patient groups with anatomical subsets of coronary disease.

Intra-Aortic Balloon Pump Counterpulsation in the Post-Resuscitation Period is Associated with Improved Functional Outcomes in Patients Surviving an Out-of-Hospital Cardiac Arrest: Insights from a Dedicated Heart Attack Centre.

BACKGROUND: Despite advances in cardiopulmonary resuscitation, functional survival remains low after out-of-hospital cardiac arrest (OOHCA). Intra-aortic balloon pump (IABP) therapy has recently been shown to augment cerebral blood flow. Whether IABP therapy in the post-resuscitation period improves functional outcomes is unknown. METHODS: We analysed 174 consecutive patients who were successfully resuscitated from an OOHCA between 2011-2013 at Harefield Hospital, London. We analysed functional status at discharge and mortality up to one year. RESULTS: A total of 55 patients (32.1%) received IABP therapy. Comparing those receiving IABP with those not receiving IABP, there was no difference in favourable functional status at discharge (49.1% vs. 57.1%, p=0.321); and mortality at one year (45.5% vs. 35.5%, p=0.164). Multivariable analyses identified IABP therapy as a strong independent predictor for favourable functional status at discharge (OR=7.51, 95% CI: 2.15-26.14, p=0.002) and this association was maintained in propensity-score adjusted analyses (OR=9.90, 95% CI: 2.11-46.33, p=0.004) and inverse probability treatment weighted analyses (OR=10.84, 95% CI: 2.75-42.69, p<0.001). However, IABP therapy was not an independent predictor for mortality at one year (HR=0.93, 95% CI: 0.52-1.65, p=0.810) and this was confirmed in both propensity-score adjusted and inverse probability treatment weighted analyses. CONCLUSIONS: In this observational analysis of patients surviving an OOHCA, the use of IABP therapy in the post-resuscitation period was associated with improved functional outcomes. This warrants further evaluation in larger prospective studies.

Subclinical and clinical hypothyroidism and non-alcoholic fatty liver disease: a cross-sectional study of a random population sample aged 18 to 65 years.

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is one of the most common disorders of the liver worldwide. Recently, a correlation between thyroid dysfunction and NAFLD has been discussed. Objective of the present study was to investigate the association between thyroid dysfunction and hepatic steatosis. METHODS: Data from 2,445 subjects (51.7% females) aged 18 to 65 years participating in a population-based cross-sectional study were assessed based on a standardized questionnaire and documentation of physical, biochemical and ultrasonographic findings. After application of exclusion criteria, a total of 1,276 subjects were included in the study collective. The influence of potential factors on the development of hepatic steatosis was assessed using multivariate logistic regression. RESULTS: The prevalence of hepatic steatosis in the study collective was 27.4% (n = 349). The serum thyroxin (TT4) concentration in subjects with hepatic steatosis was reduced (p =0.0004). Adjusting for age, or BMI, there was an increased prevalence of hepatic steatosis in subjects with reduced TT4 concentrations (p = 0.0143; p = < .0001). CONCLUSIONS: The findings of the present study confirm an association between both subclinical and clinical hypothyroidism and hepatic steatosis.

Comparison of Acoustic Structure Quantification (ASQ), shearwave elastography and histology in patients with diffuse hepatopathies.

BACKGROUND: Objective of the study was to evaluate the diagnostic value of novel ultrasonographic modalities in comparison with simultaneously performed liver biopsy. METHODS: The results of simultaneously performed examinations using Acoustic Structure Quantification (ASQ), Virtual Touch Imaging and Quantification (VTIQ) and Virtual Touch Tissue Quantification (VTTQ) were compared with the findings of liver biopsy in patients with a wide variety of diffuse hepatopathies (n = 51). The histologically determined fibrosis stage according to Desmet and Scheuer was compared with quantitative measurements returned by the ultrasonographic imaging modalities. RESULTS: No statistically significant correlation with histologically determined fibrosis stage could be identified for any measurements returned using ASQ. Increasing severity of hepatic steatosis, however, was associated with a reduction in the focal disturbance (FD) ratio (r = -0.55; p < 0.0001). The shearwave velocities measured using VTTQ satisfyingly correlated with fibrosis stage (r = 0.56; p > 0.0001). Fibrosis stages > F2 were associated with an area under the curve (AUC) of 0.94 (95%-CI:0.84-0.99). A cut-off value for shearwave velocity of 1.66 m/s was determined with a sensitivity of 100% and a specificity of 84 %. VTIQ showed a less pronounced but acceptable correlation with fibrosis stage (r = 0.35; p = 0.0154). For fibrosis stages > F2 analysis showed an AUC of 0.84 (95%-CI:0.70-0.93). The cut-off value was 1.82 m/s with a sensitivity of 100% and a specificity of 58 %. CONCLUSION: While ASQ showed no diagnostic advantage in our patient collective, VTTQ showed high reliability for determining severe liver fibrosis in a group of patients with diffuse liver diseases of different etiology.

Fasting time and lipid parameters: association with hepatic steatosis--data from a random population sample.

BACKGROUND: Current guidelines recommend measuring plasma lipids in fasting patients. Recent studies, however, suggest that variation in plasma lipid concentrations secondary to fasting time may be minimal. Objective of the present study was to investigate the impact of fasting time on plasma lipid concentrations (total cholesterol, HDL and LDL cholesterol, triglycerides). A second objective was to determine the effect of non-alcoholic fatty liver disease exerted on the above-mentioned lipid levels. METHOD: Subjects participating in a population-based cross-sectional study (2,445 subjects; 51.7% females) were questioned at time of phlebotomy regarding duration of pre-phlebotomy fasting. Total cholesterol, LDL and HDL cholesterol, and triglycerides were determined and correlated with length of fasting. An upper abdominal ultrasonographic examination was performed and body-mass index (BMI) and waist-to-hip ratio (WHR) were calculated. Subjects were divided into three groups based on their reported fasting periods of 1-4 h, 4-8 h and > 8 h. After application of the exclusion criteria, a total of 1,195 subjects (52.4% females) were included in the study collective. The Kruskal-Wallis test was used for continuous variables and the chi-square test for categorical variables. The effects of age, BMI, WHR, alcohol consumption, fasting time and hepatic steatosis on the respective lipid variables were analyzed using multivariate logistic regression. RESULTS: At multivariate analysis, fasting time was associated with elevated triglycerides (p = 0.0047 for 1-4 h and p = 0.0147 for 4-8 h among females; p < 0.0001 for 1-4 h and p = 0.0002 for 4-8 h among males) and reduced LDL cholesterol levels (p = 0.0003 for 1-4 h and p = 0.0327 for 4-8 h among males). Among males, hepatic steatosis represents an independent factor affecting elevated total cholesterol (p = 0.0278) and triglyceride concentrations (p = 0.0002). CONCLUSION: Total and HDL cholesterol concentrations are subject to slight variations in relation to the duration of the pre-phlebotomy fasting period. LDL cholesterol and triglycerides exhibit highly significant variability; the greatest impact is seen with the triglycerides. Fasting time represents an independent factor for reduced LDL cholesterol and elevated triglyceride concentrations. There is a close association between elevated lipids and hepatic steatosis.

Assessment of liver size by ultrasonography.

BACKGROUND: To determine liver span sonographically in a randomly selected population sample and identify factors that affect liver size. METHODS: A total of 1,789 subjects (963 females, 826 males; mean age 41.8 ± 12.8 years) underwent sonographic examination of the liver in the midclavicular line to determine liver span. Subjects underwent physical examination and blood tests and completed a standardized interview questionnaire. RESULTS: The average liver span in the midclavicular line for the overall collective was 15.0 ± 1.5 cm; the average for females was 14.9 ± 1.6 cm and 15.1 ± 1.5 cm for males. Liver span exceeded 16 cm in 24.3% of subjects. Results of the multivariate analysis showed that, of the factors potentially influencing liver span, gender, age, body mass index, body height, fatty liver (p < 0.0001), waist-to-hip ratio (p = 0.015), and metabolic syndrome (p = 0.032) are significant. By contrast, diabetes mellitus, alcohol consumption, tobacco consumption, physical activity, and laboratory findings showed no influence. CONCLUSIONS: Sonographic measurement of liver span in the midclavicular line is a simple method for routine clinical use. Gender, age, body mass index, waist-to-hip ratio, body height, hepatic steatosis, and metabolic syndrome are factors associated with liver span.

HaploCatcher: An R package for prediction of haplotypes.

Wheat (Triticum aestivum L.) is crucial to global food security but is often threatened by diseases, pests, and environmental stresses. Wheat-stem sawfly (Cephus cinctus Norton) poses a major threat to food security in the United States, and solid-stem varieties, which carry the stem-solidness locus (Sst1), are the main source of genetic resistance against sawfly. Marker-assisted selection uses molecular markers to identify lines possessing beneficial haplotypes, like that of the Sst1 locus. In this study, an R package titled "HaploCatcher" was developed to predict specific haplotypes of interest in genome-wide genotyped lines. A training population of 1056 lines genotyped for the Sst1 locus, known to confer stem solidness, and genome-wide markers was curated to make predictions of the Sst1 haplotypes for 292 lines from the Colorado State University wheat breeding program. Predicted Sst1 haplotypes were compared to marker-derived haplotypes. Our results indicated that the training set was substantially predictive, with kappa scores of 0.83 for k-nearest neighbors and 0.88 for random forest models. Forward validation on newly developed breeding lines demonstrated that a random forest model, trained on the total available training data, had comparable accuracy between forward and cross-validation. Estimated group means of lines classified by haplotypes from PCR-derived markers and predictive modeling did not significantly differ. The HaploCatcher package is freely available and may be utilized by breeding programs, using their own training populations, to predict haplotypes for whole-genome sequenced early generation material.

Artificial intelligence methods for improved detection of undiagnosed heart failure with preserved ejection fraction.

AIM: Heart failure with preserved ejection fraction (HFpEF) remains under-diagnosed in clinical practice despite accounting for nearly half of all heart failure (HF) cases. Accurate and timely diagnosis of HFpEF is crucial for proper patient management and treatment. In this study, we explored the potential of natural language processing (NLP) to improve the detection and diagnosis of HFpEF according to the European Society of Cardiology (ESC) diagnostic criteria. METHODS AND RESULTS: In a retrospective cohort study, we used an NLP pipeline applied to the electronic health record (EHR) to identify patients with a clinical diagnosis of HF between 2010 and 2022. We collected demographic, clinical, echocardiographic and outcome data from the EHR. Patients were categorized according to the left ventricular ejection fraction (LVEF). Those with LVEF ≥50% were further categorized based on whether they had a clinician-assigned diagnosis of HFpEF and if not, whether they met the ESC diagnostic criteria. Results were validated in a second, independent centre. We identified 8606 patients with HF. Of 3727 consecutive patients with HF and LVEF ≥50% on echocardiogram, only 8.3% had a clinician-assigned diagnosis of HFpEF, while 75.4% met ESC criteria but did not have a formal diagnosis of HFpEF. Patients with confirmed HFpEF were hospitalized more frequently; however the ESC criteria group had a higher 5-year mortality, despite being less comorbid and experiencing fewer acute cardiovascular events. CONCLUSIONS: This study demonstrates that patients with undiagnosed HFpEF are an at-risk group with high mortality. It is possible to use NLP methods to identify likely HFpEF patients from EHR data who would likely then benefit from expert clinical review and complement the use of diagnostic algorithms.

Sonographically guided puncture of the pancreas: incidence of complications, and risk factors.

PURPOSE: Data yielded by transabdominal ultrasound-guided puncture techniques are valuable for determining the malignancy of inoperable mass lesions of the pancreas. In this study we analyzed the incidence of complications and the risk factors. METHODS: A total of 430 punctures of the pancreas were performed for 281 patients. Risk factors were prospectively assessed and complications were recorded. All punctures were sonographically guided. RESULTS: The 281 patients underwent a total of 351 puncture procedures including 430 punctures and 901 passes. The maximum diameter of the pancreatic mass lesion was documented; the mean diameter was 48.3 ± 29.1 mm. 75.8 % of punctures were performed with a needle diameter of 0.7-0.95 mm, and 23.0 % of punctures were performed as cutting biopsies producing a tissue sample 1.2 or 1.6 mm in diameter. In 77.8 % of punctures, one puncture was performed, and in 21.9 %, two punctures were performed. Three punctures were performed for one patient (0.3 %) only. The incidence of major complications was 0.3 %. None of the assessed risk factors was associated with an elevated incidence of complications. CONCLUSION: Our findings demonstrate the safety of transabdominal percutaneous puncture of the pancreas but do not enable conclusions to be drawn with regard to individual risk factors.

Utilization of a publicly available diversity panel in genomic prediction of Fusarium head blight resistance traits in wheat.

Fusarium head blight (FHB) is an economically and environmentally concerning disease of wheat (Triticum aestivum L). A two-pronged approach of marker-assisted selection coupled with genomic selection has been suggested when breeding for FHB resistance. A historical dataset comprised of entries in the Southern Uniform Winter Wheat Scab Nursery (SUWWSN) from 2011 to 2021 was partitioned and used in genomic prediction. Two traits were curated from 2011 to 2021 in the SUWWSN: percent Fusarium damaged kernels (FDK) and deoxynivalenol (DON) content. Heritability was estimated for each trait-by-environment combination. A consistent set of check lines was drawn from each year in the SUWWSN, and k-means clustering was performed across environments to assign environments into clusters. Two clusters were identified as FDK and three for DON. Cross-validation on SUWWSN data from 2011 to 2019 indicated no outperforming training population in comparison to the combined dataset. Forward validation for FDK on the SUWWSN 2020 and 2021 data indicated a predictive accuracy r ≈ 0.58 $r \approx 0.58$ and r ≈ 0.53 $r \approx 0.53$ , respectively. Forward validation for DON indicated a predictive accuracy of r ≈ 0.57 $r \approx 0.57$ and r ≈ 0.45 $r \approx 0.45$ , respectively. Forward validation using environments in cluster one for FDK indicated a predictive accuracy of r ≈ 0.65 $r \approx 0.65$ and r ≈ 0.60 $r \approx 0.60$ , respectively. Forward validation using environments in cluster one for DON indicated a predictive accuracy of r ≈ 0.67 $r \approx 0.67$ and r ≈ 0.60 $r \approx 0.60$ , respectively. These results indicated that selecting environments based on check performance may produce higher forward prediction accuracies. This work may be used as a model for utilizing public resources for genomic prediction of FHB resistance traits across public wheat breeding programs.

Multi-target genome editing reduces polyphenol oxidase activity in wheat (Triticum aestivum L.) grains.

Introduction: Polyphenol oxidases (PPO) are dual activity metalloenzymes that catalyse the production of quinones. In plants, PPO activity may contribute to biotic stress resistance and secondary metabolism but is undesirable for food producers because it causes the discolouration and changes in flavour profiles of products during post-harvest processing. In wheat (Triticum aestivum L.), PPO released from the aleurone layer of the grain during milling results in the discolouration of flour, dough, and end-use products, reducing their value. Loss-of-function mutations in the PPO1 and PPO2 paralogous genes on homoeologous group 2 chromosomes confer reduced PPO activity in the wheat grain. However, limited natural variation and the proximity of these genes complicates the selection of extremely low-PPO wheat varieties by recombination. The goal of the current study was to edit all copies of PPO1 and PPO2 to drive extreme reductions in PPO grain activity in elite wheat varieties. Results: A CRISPR/Cas9 construct with one single guide RNA (sgRNA) targeting a conserved copper binding domain was used to edit all seven PPO1 and PPO2 genes in the spring wheat cultivar 'Fielder'. Five of the seven edited T1 lines exhibited significant reductions in PPO activity, and T2 lines had PPO activity up to 86.7% lower than wild-type. The same construct was transformed into the elite winter wheat cultivars 'Guardian' and 'Steamboat', which have five PPO1 and PPO2 genes. In these varieties PPO activity was reduced by >90% in both T1 and T2 lines. In all three varieties, dough samples from edited lines exhibited reduced browning. Discussion: This study demonstrates that multi-target editing at late stages of variety development could complement selection for beneficial alleles in crop breeding programs by inducing novel variation in loci inaccessible to recombination.

Patient randomised controlled trial of technology enabled strategies to promote treatment adherence in liver transplantation: rationale and design of the TEST trial.

BACKGROUND AND AIMS: Liver transplantation is a life-saving procedure for end-stage liver disease. However, post-transplant medication regimens are complex and non-adherence is common. Post-transplant medication non-adherence is associated with graft rejection, which can have long-term adverse consequences. Transplant centres are equipped with clinical staff that monitor patients post-transplant; however, digital health tools and proactive immunosuppression adherence monitoring has potential to improve outcomes. METHODS AND ANALYSIS: This is a patient-randomised prospective clinical trial at three transplant centres in the Northeast, Midwest and South to investigate the effects of a remotely administered adherence programme compared with usual care. The programme monitors potential non-adherence largely levering text message prompts and phenotypes the nature of the non-adhere as cognitive, psychological, medical, social or economic. Additional reminders for medications, clinical appointments and routine self-management support are incorporated to promote adherence to the entire medical regimen. The primary study outcome is medication adherence via 24-hour recall; secondary outcomes include additional medication adherence (ASK-12 self-reported scale, regimen knowledge scales, tacrolimus values), quality of life, functional health status and clinical outcomes (eg, days hospitalised). Study implementation, acceptability, feasibility, costs and potential cost-effectiveness will also be evaluated. ETHICS AND DISSEMINATION: The University of Pennsylvania Review Board has approved the study as the single IRB of record (protocol # 849575, V.1.4). Results will be published in peer-reviewed journals and summaries will be provided to study funders. TRIAL REGISTRATION NUMBER: NCT05260268.

Reproducibility of cardiac power output and other cardiopulmonary exercise indices in patients with chronic heart failure.

Cardiac power output is a direct measure of overall cardiac function that integrates both flow- and pressure-generating capacities of the heart. The present study assessed the reproducibility of cardiac power output and other more commonly reported cardiopulmonary exercise variables in patients with chronic heart failure. Metabolic, ventilatory and non-invasive (inert gas re-breathing) central haemodynamic measurements were undertaken at rest and near-maximal exercise of the modified Bruce protocol in 19 patients with stable chronic heart failure. The same procedure was repeated 7 days later to assess reproducibility. Cardiac power output was calculated as the product of cardiac output and mean arterial pressure. Resting central haemodynamic variables demonstrate low CV (coefficient of variation) (ranging from 3.4% for cardiac output and 5.6% for heart rate). The CV for resting metabolic and ventilatory measurements ranged from 8.2% for respiratory exchange ratio and 14.2% for absolute values of oxygen consumption. The CV of anaerobic threshold, peak oxygen consumption, carbon dioxide production and respiratory exchange ratio ranged from 3.8% (for anaerobic threshold) to 6.4% (for relative peak oxygen consumption), with minute ventilation having a CV of 11.1%. Near-maximal exercise cardiac power output and cardiac output had CVs of 4.1 and 2.2%, respectively. Cardiac power output demonstrates good reproducibility suggesting that there is no need for performing more than one cardiopulmonary exercise test. As a direct measure of cardiac function (dysfunction) and an excellent prognostic marker, it is strongly advised in the assessment of patients with chronic heart failure undergoing cardiopulmonary exercise testing.

Percutaneous ultrasonographically guided liver punctures: an analysis of 1961 patients over a period of ten years.

BACKGROUND: Ultrasonographically guided punctures of the liver represent a decisive tool in the diagnosis of many diseases of the liver. Objective of the study was to determine the extent to which the complication rate for ultrasonographically guided punctures of the liver is affected by less comprehensively studied risk factors. METHODS: A total of 2,229 liver biopsies were performed in 1,961 patients (55.5% males; 44.5% females). We recorded actual complications and assessed the following risk factors: needle gauge, puncture technique, examiner experience, coagulation status, puncture target (focal lesion versus parenchyma), lesion size, patient sex and age. RESULTS: he rate of complications stood at 1.2% (n = 27), of which 0.5% (n = 12) were major and 0.7% (n = 15) minor complications. A significant increase in complications involving bleeding was observed with larger-gauge needles compared with smaller-gauge needles and for cutting biopsy punctures compared with aspiration biopsies (Menghini technique). In the bivariate analysis complications were 2.7 times more frequent in procedures performed by experienced examiners compared with those with comparatively less experience. Lower values for Quick's test and higher partial thromboplastin times were associated with a higher rate of bleeding. Neither the puncture target, lesion size or patient sex exerted any measurable influence on the puncture risk. Advanced patient age was associated with a higher rate of complications involving bleeding. CONCLUSIONS: Our study helps to establish the importance of potential and less comprehensively studied risk factors and may contribute to further reduction in complications rates in routine clinical practice.

Utilizing genomics and historical data to optimize gene pools for new breeding programs: A case study in winter wheat.

With the rapid generation and preservation of both genomic and phenotypic information for many genotypes within crops and across locations, emerging breeding programs have a valuable opportunity to leverage these resources to 1) establish the most appropriate genetic foundation at program inception and 2) implement robust genomic prediction platforms that can effectively select future breeding lines. Integrating genomics-enabled breeding into cultivar development can save costs and allow resources to be reallocated towards advanced (i.e., later) stages of field evaluation, which can facilitate an increased number of testing locations and replicates within locations. In this context, a reestablished winter wheat breeding program was used as a case study to understand best practices to leverage and tailor existing genomic and phenotypic resources to determine optimal genetics for a specific target population of environments. First, historical multi-environment phenotype data, representing 1,285 advanced breeding lines, were compiled from multi-institutional testing as part of the SunGrains cooperative and used to produce GGE biplots and PCA for yield. Locations were clustered based on highly correlated line performance among the target population of environments into 22 subsets. For each of the subsets generated, EMMs and BLUPs were calculated using linear models with the 'lme4' R package. Second, for each subset, TPs representative of the new SC breeding lines were determined based on genetic relatedness using the 'STPGA' R package. Third, for each TP, phenotypic values and SNP data were incorporated into the 'rrBLUP' mixed models for generation of GEBVs of YLD, TW, HD and PH. Using a five-fold cross-validation strategy, an average accuracy of r = 0.42 was obtained for yield between all TPs. The validation performed with 58 SC elite breeding lines resulted in an accuracy of r = 0.62 when the TP included complete historical data. Lastly, QTL-by-environment interaction for 18 major effect genes across three geographic regions was examined. Lines harboring major QTL in the absence of disease could potentially underperform (e.g., Fhb1 R-gene), whereas it is advantageous to express a major QTL under biotic pressure (e.g., stripe rust R-gene). This study highlights the importance of genomics-enabled breeding and multi-institutional partnerships to accelerate cultivar development.