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Globally, we are applying excessive nitrogen (N) fertilizers to our agricultural crops, which ultimately causes nitrogen pollution to our ecosphere. The atmosphere is polluted by N₂O and NO(x) gases that directly and indirectly increase atmospheric warming and climate change. Nitrogen is also leached from agricultural lands as the water-soluble form NO₃⁻, which increases nutrient overload in rivers, lakes, and oceans, causing \"dead zones\", reducing property values and the diversity of aquatic life, and damaging our drinking water and aquatic-associated industries such as fishing and tourism. Why do some countries show reductions in fertilizer use while others show increasing use? What N fertilizer application reductions could occur, without compromising crop yields? And what are the economic and environmental benefits of using directed nutrient management strategies?

Temperatures higher than the optimum negatively affects plant growth and development. Tolerance to high temperature is a complex process that involves several pathways. Understanding this process, especially in crops such as rice, is essential to prepare for predicted climate changes due to global warming. Here, we show that OsMYB55 is induced by high temperature and overexpression of OsMYB55 resulted in improved plant growth under high temperature and decreased the negative effect of high temperature on grain yield. Transcriptome analysis revealed an increase in expression of several genes involved in amino acids metabolism. We demonstrate that OsMYB55 binds to the promoter regions of target genes and directly activates expression of some of those genes including glutamine synthetase (OsGS1;2) glutamine amidotransferase (GAT1) and glutamate decarboxylase 3 (GAD3). OsMYB55 overexpression resulted in an increase in total amino acid content and of the individual amino acids produced by the activation of the above mentioned genes and known for their roles in stress tolerance, namely L-glutamic acid, GABA and arginine especially under high temperature condition. In conclusion, overexpression of OsMYB55 improves rice plant tolerance to high temperature, and this high tolerance is associated with enhanced amino acid metabolism through transcription activation.

The interaction between phytohormones is an important mechanism which controls growth and developmental processes in plants. Deciphering these interactions is a crucial step in helping to develop crops with enhanced yield and resistance to environmental stresses. Controlling the expression level of OsAP2-39 which includes an APETALA 2 (AP2) domain leads to phenotypic changes in rice. Overexpression of OsAP2-39 leads to a reduction in yield by decreasing the biomass and the number of seeds in the transgenic rice lines. Global transcriptome analysis of the OsAP2-39 overexpression transgenic rice revealed the upregulation of a key abscisic acid (ABA) biosynthetic gene OsNCED-I which codes for 9-cis-epoxycarotenoid dioxygenase and leads to an increase in the endogenous ABA level. In addition to OsNCED-1, the gene expression analysis revealed the upregulation of a gene that codes for the Elongation of Upper most Internode (EUI) protein, an enzyme that catalyzes 16α, 17-epoxidation of non-13-hydroxylated GAs, which has been shown to deactivate gibberellins (GAs) in rice. The exogenous application of GA restores the wild-type phenotype in the transgenic line and ABA application induces the expression of EUI and suppresses the expression of OsAP2-39 in the wild-type line. These observations clarify the antagonistic relationship between ABA and GA and illustrate a mechanism that leads to homeostasis of these hormones. In vivo and in vitro analysis showed that the expression of both OsNCED-1 and EUI are directly controlled by OsAP2-39. Together, these results reveal a novel mechanism for the control of the ABA/GA balance in rice which is regulated by OsAP2-39 that in turn regulates plant growth and seed production.

Background There is an unmet clinical need for minimally invasive diagnostic tests to improve the detection of grade group (GG) ≥3 prostate cancer relative to prostate antigen‐specific risk calculators. We determined the accuracy of the blood‐based extracellular vesicle (EV) biomarker assay (EV Fingerprint test) at the point of a prostate biopsy decision to predict GG ≥3 from GG ≤2 and avoid unnecessary biopsies. Methods This study analyzed 415 men referred to urology clinics and scheduled for a prostate biopsy, were recruited to the APCaRI 01 prospective cohort study. The EV machine learning analysis platform was used to generate predictive EV models from microflow data. Logistic regression was then used to analyze the combined EV models and patient clinical data and generate the patients' risk score for GG ≥3 prostate cancer. Results The EV‐Fingerprint test was evaluated using the area under the curve (AUC) in discrimination of GG ≥3 from GG ≤2 and benign disease on initial biopsy. EV‐Fingerprint identified GG ≥3 cancer patients with high accuracy (0.81 AUC) at 95% sensitivity and 97% negative predictive value. Using a 7.85% probability cutoff, 95% of men with GG ≥3 would have been recommended a biopsy while avoiding 144 unnecessary biopsies (35%) and missing four GG ≥3 cancers (5%). Conversely, a 5% cutoff would have avoided 31 unnecessary biopsies (7%), missing no GG ≥3 cancers (0%). Conclusions EV‐Fingerprint accurately predicted GG ≥3 prostate cancer and would have significantly reduced unnecessary prostate biopsies. We developed an accurate diagnostic blood test for grade group (GG) ≥3 prostate cancer that comprises the generation of a microflow cytometry dataset of three prostate cancer extracellular vesicle (EV) biomarkers, analysis with a novel machine learning algorithm to generate predictive EV models, and logistic regression analysis of these models with patient clinical data to calculate the risk score for the probability of GG ≥3 prostate cancer.

The current prostate cancer (PCa) screen test, prostate-specific antigen (PSA), has a high sensitivity for PCa but low specificity for high-risk, clinically significant PCa (csPCa), resulting in overdiagnosis and overtreatment of non-csPCa. Early identification of csPCa while avoiding unnecessary biopsies in men with non-csPCa is challenging. We built an optimized machine learning platform (ClarityDX) and showed its utility in generating models predicting csPCa. Integrating the ClarityDX platform with blood-based biomarkers for clinically significant PCa and clinical biomarker data from a 3448-patient cohort, we developed a test to stratify patients’ risk of csPCa; called ClarityDX Prostate. When predicting high risk cancer in the validation cohort, ClarityDX Prostate showed 95% sensitivity, 35% specificity, 54% positive predictive value, and 91% negative predictive value, at a ≥ 25% threshold. Using ClarityDX Prostate at this threshold could avoid up to 35% of unnecessary prostate biopsies. ClarityDX Prostate showed higher accuracy for predicting the risk of csPCa than PSA alone and the tested model-based risk calculators. Using this test as a reflex test in men with elevated PSA levels may help patients and their healthcare providers decide if a prostate biopsy is necessary.

PurposeThe Alberta Prostate Cancer Research Initiative (APCaRI) Registry and Biorepository was established in 2014 by the APCaRI to facilitate the collection of clinical and patient-reported data, biospecimen, to measure prostate cancer outcomes and to support the development and clinical translation of innovative technologies to better diagnose and predict outcomes for patients with prostate cancer.ParticipantsMen suspected with prostate cancer and referred to Urology centres in Alberta were enrolled in the APCaRI 01 study, while men with a prior prostate cancer diagnosis participated in the APCaRI 03 study from 1 July 2014 to 30 June 2019. The APCaRI Registry and Biorepository links biospecimens and data from a wide representation of patients drawn from an Alberta population of more than 4 million.Findings to dateFrom 1 July 2014 to 30 June 2019, total APCaRI 01 and 03 study recruitment was 3754 men; 142 (4%) of these men withdrew in full, 65 men (2%) withdrew biospecimens and 123 men (3%) died of any cause. Over this same time, 8677 patient-reported outcome measure (PROM) surveys and 7368 biospecimens were collected and are available from the registry and biorepository, respectively. The data entry error rate was 0.8% and 0.95% for critical and non-critical values, respectively, and 1.8% for patient-reported surveys.Future plansThe APCaRI Registry and Biorepository will collect longitudinal data and PROM surveys until 2024, patient outcomes up to 25 years after recruitment and biospecimen storage for up to 25 years. The APCaRI cohorts will continue to provide data and samples to researchers conducting retrospective studies. The richness of the data and biospecimens will complement many different research questions, ultimately to improve the quality of care for men with prostate cancer.

What are the next steps in engineering crop plants that fix nitrogen and make their own fertilizer? Nitrogen availability is limiting to plant growth and has long been overcome through applications of synthetic nitrogen-rich fertilizer. This has revolutionized crop yield and food production worldwide, but at substantial economic and environmental cost (fixed N2; a $100 billion per year global industry and environmental nitrogen pollution). Indeed, in April, the Edinburgh Declaration on Reactive Nitrogen was the most recent call for global action to address this source of nitrogen pollution. At the same time, the Bill and Melinda Gates Foundation convened a small meeting of international researchers to assess the way forward in reducing dependence on fertilizers through engineering crop plants that “fix” nitrogen themselves to sustain their growth and yield. The discussions of recent advances indicate that there are indeed viable options to achieve this goal.

While chemotherapy is a key treatment strategy for many solid tumors, it is rarely curative, and most tumor cells eventually become resistant. Because of this, there is an unmet need to develop systemic treatments that capitalize on the unique mutational landscape of each patient’s tumor. The most frequently mutated protein in cancer, p53, has a role in nearly all cancer subtypes and tumorigenesis stages and therefore is one of the most promising molecular targets for cancer treatment. Unfortunately, drugs targeting p53 have seen little clinical success despite promising preclinical data. Most of these drug compounds target specific aspects of p53 inactivation, such as through inhibiting negative regulation by the mouse double minute (MDM) family of proteins. These treatment strategies fail to address cancer cells’ adaptation mechanisms and ignore the impact that p53 loss has on the entire p53 network. However, recent gene therapy successes show that targeting the p53 network and cellular dysfunction caused by p53 inactivation is now possible and may soon translate into successful clinical responses. In this review, we discuss p53 signaling complexities in cancer that have hindered the development and use of p53-targeted drugs. We also describe several current therapeutics reporting promising preclinical and clinical results.

Over the past half century, the use of nitrogen (N) fertilizers has markedly increased crop yields, but with considerable negative effects on the environment and human health. Consequently, there has been a strong push to reduce the amount of N fertilizer used by maximizing the nitrogen use efficiency (NUE) of crops. One approach would be to use classical genetics to improve the NUE of a crop plant. This involves both conventional breeding and quantitative trait loci (QTL) mapping in combination with marker-assisted selection (MAS) to track key regions of the chromosome that segregate for NUE. To achieve this goal, one of initial steps is to characterize the NUE-associated genes, then use the profiles of specific genes to combine plant physiology and genetics to improve plant performance. In this study, on the basis of genetic homology and expression analysis, barley candidate genes from a variety of families that exhibited potential roles in enhancing NUE were identified and mapped. We then performed an analysis of QTLs associated with NUE in field trials and further analyzed their map-location data to narrow the search for these candidate genes. These results provide a novel insight on the identification of NUE genes and for the future prospects, will lead to a more thorough understanding of physiological significances of the diverse gene families that may be associated with NUE in barley.

BACKGROUND AND AIMS: Nitrogen-use efficiency (NUE) of cereals needs to be improved by nitrogen (N) management, traditional plant breeding methods and/or biotechnology, while maintaining or, optimally, increasing crop yields. The aims of this study were to compare spring-barley genotypes grown on different nitrogen levels in field and growth-chamber conditions to determine the effects on N uptake (NUpE) and N utilization efficiency (NUtE) and ultimately, NUE. METHODS: Morphological characteristics, seed yield and metabolite levels of 12 spring barley (Hordeum vulgare) genotypes were compared when grown at high and low nitrogen levels in field conditions during the 2007 and 2008 Canadian growing seasons, and in potted and hydroponic growth-chamber conditions. Genotypic NUpE, NUtE and NUE were calculated and compared between field and growth-chamber environments. KEY RESULTS: Growth chamber and field tests generally showed consistent NUE characteristics. In the field, Vivar, Excel and Ponoka, showed high NUE phenotypes across years and N levels. Vivar also had high NUE in growth-chamber trials, showing NUE across complex to simplistic growth environments. With the high NUE genotypes grown at low N in the field, NUtE predominates over NUpE. N metabolism-associated amino acid levels were different between roots (elevated glutamine) and shoots (elevated glutamate and alanine) of hydroponically grown genotypes. In field trials, metabolite levels were different between Kasota grown at high N (elevated glutamine) and Kasota at low N plus Vivar at either N condition. CONCLUSIONS: Determining which trait(s) or gene(s) to target to improve barley NUE is important and can be facilitated using simplified growth approaches to help determine the NUE phenotype of various genotypes. The genotypes studied showed similar growth and NUE characteristics across field and growth-chamber tests demonstrating that simplified, low-variable growth environments can help pinpoint genetic targets for improving spring barley NUE.