Showing papers by "Mark E. Cooper published in 2023"

Two decades of harnessing standing genetic variation for physiological traits to improve drought tolerance in maize (Zea mays L.).

Abstract: We review approaches to maize breeding for improved drought tolerance during flowering and grain filling in central and western US corn belt and place our findings in context of results from public breeding. Here we show that after two decades of dedicated breeding efforts, the rate of crop improvement under drought increased from 6.2 to 7.5 g m -2 y -1 closing the genetic gain gap with respect to the 8.6 g m -2 y -1 observed under water sufficient conditions. The improvement relative to the long-term genetic gain was possible by harnessing favorable alleles for physiological traits available in the reference population of genotypes. Experimentation in managed stress environments that maximized the genetic correlation with target environments was key for breeders to identify and select for these alleles. We also show that the embedding physiological understanding within genomic selection methods via crop growth models can hasten genetic gain under drought. We estimate a prediction accuracy differential (Δr) above current prediction approaches of ~ 30% (Δr = 0.11, r = 0.38), which increase with increasing complexity of the trait x environment system as estimated by Shannon Information. We propose this framework to inform breeding strategies for drought stress across geographies and crops.

Glucocorticoid-Induced Psychosis in Children and Adolescents: A Systematic Review.

Abstract: Objectives: Knowledge is limited regarding the adverse effects of therapeutic glucocorticoids on pediatric mental health outcomes. Glucocorticoid-induced psychosis (GIP) is a rare but severe side effect of high-dose glucocorticoid therapy in children and adolescents. This study identified reported pediatric cases of GIP, based on DSM-5 criteria, and defined its presentation, treatments, and outcomes. Methods: A systematic review was completed in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, including pediatric patients with incident psychosis following glucocorticoid treatment. Patient demographics, clinical presentation, interventions, outcomes, and long-term management were extracted from individual cases. Results: Of 1131 articles screened, 28 reports were included, comprising of 31 patients. The mean age was 13 years, and 61% of patients were male. The most common medical illnesses requiring administration of high dose glucocorticoids were asthma (23%) and acute lymphoblastic leukemia (23%). The most common glucocorticoid used was prednisone (35%), and most patients (91%) received doses greater than or equal to 40 mg/day of prednisone. The range of time to symptom onset was 1 day to 7 months. Hallucinations alone (45%) were the most reported feature of GIP. Glucocorticoids were discontinued in 52% of cases, reduced in dosage in 32%, and 81% of affected patients were prescribed psychotropic medications. Long-term management plans and prophylactic psychotropic use were not mentioned in 52% of cases. Symptoms resolved in 90% of patients, and the majority (71%) had no recurrence of psychiatric symptoms. Conclusions: GIP can generally be managed by tapering the causative agent with adjunctive second-generation antipsychotics if psychotic symptoms persist. All patients in this review had complete resolution or improvement of their psychotic symptoms; however, there is likely reporting bias due to the expected underreporting of negative outcomes. Managing clinicians must take a circumspect approach when prescribing high-dose glucocorticoids to minimize the risk of serious but preventable side effects.

Root system growth and function response to soil temperature in maize (Zea mays L.)

Abstract: Crop adaptation to the mixture of environments that defines the target population of environments is the result from a balanced resource allocation between roots, shoots and reproductive organs. Root growth places a critical role in the determination of this balance. Root growth and function responses to temperature can determine the strength of roots as sinks but also influence the crop’s ability to uptake water and nutrients. Surprisingly, this behavior has not been studied in maize since the middle of the last century, and the genetic determinants are unknown. Low temperatures often recorded in deep soil layers limit root growth and soil exploration and may constitute a bottleneck towards increasing drought tolerance, nitrogen recovery, sequestration of carbon and productivity in maize. High throughput phenotyping (HTP) systems were developed to investigate these responses and to examine genetic variability therein across diverse maize germplasm. Here we show that there is: 1) genetic variation of root growth under low temperature and below 10°C, and 2) genotypic variation in water transport under low temperature. Using simulation, we demonstrate that the measured variation for both traits contribute to drought tolerance and explain important components of yield variation in the US corn-belt. The trait set examined herein and HTP platform developed for its characterization reveal a unique opportunity to remove a major bottleneck for crop improvement, and adaptation to climate change.

Reduced methylation correlates with diabetic nephropathy risk in type 1 diabetes

Abstract: Diabetic nephropathy (DN) is a polygenic disorder with few risk variants showing robust replication in large-scale genome-wide association studies. To understand the role of DNA methylation, it is important to have the prevailing genomic view to distinguish key sequence elements that influence gene expression. This is particularly challenging for DN because genome-wide methylation patterns are poorly defined. While methylation is known to alter gene expression, the importance of this causal relationship is obscured by array-based technologies since coverage outside promoter regions is low. To overcome these challenges, we performed methylation sequencing using leukocytes derived from participants of the Finnish Diabetic Nephropathy (FinnDiane) type 1 diabetes (T1D) study (n = 39) that was subsequently replicated in a larger validation cohort (n = 296). Gene body–related regions made up more than 60% of the methylation differences and emphasized the importance of methylation sequencing. We observed differentially methylated genes associated with DN in 3 independent T1D registries originating from Denmark (n = 445), Hong Kong (n = 107), and Thailand (n = 130). Reduced DNA methylation at CTCF and Pol2B sites was tightly connected with DN pathways that include insulin signaling, lipid metabolism, and fibrosis. To define the pathophysiological significance of these population findings, methylation indices were assessed in human renal cells such as podocytes and proximal convoluted tubule cells. The expression of core genes was associated with reduced methylation, elevated CTCF and Pol2B binding, and the activation of insulin-signaling phosphoproteins in hyperglycemic cells. These experimental observations also closely parallel methylation-mediated regulation in human macrophages and vascular endothelial cells.

4 Nurse-led interventions for people with multimorbidity: what are they and how do they improve outcomes? A mixed-methods systematic review

Abstract:

Background

People with 2 or more chronic conditions (multimorbidity) are at risk of receiving fragmented and inefficient care. In order to develop a nurse-led intervention for people with multimorbidity and palliative conditions, we sought to explore the types of existing nurse-led multimorbidity interventions and what outcomes were positively affected by them.

Methods

Mixed-methods systematic review following Joanna Briggs Institute (JBI) methodology. Cochrane CENTRAL, CINAHL, Embase and MEDLINE were searched from inception in October 2020 alongside grey literature. Quality appraisal was conducted using JBI tools; low-quality studies were not excluded but did not generate any novel findings in sensitivity analyses. Interventions were classified using adapted Cochrane EPOC taxonomy and outcomes were mapped to the Core Outcome Set for Multimorbidity Research. PROSPERO ID: CRD42020197956.

Results

20 eligible studies were included. Case-management or transitional care interventions were most common, and often featured nurses in advanced practice, supported self-management, individualised care-planning and care coordination. Predictive modelling to identify people at high-risk of healthcare utilisation was also common. Positive effects were most consistently reported in relation to person-centred outcomes (such as patient-perceived quality of care, quality of life, quality of communication with healthcare providers), with mixed effects observed on healthcare utilisation, mortality and other core outcomes.

Conclusions

Nurse-led multimorbidity interventions are agreeable to patients but their effects on service use and costs are mixed. Complexity in populations and intervention types mean that localised development and iterative evaluation of interventions may be the most effective approach to improving outcomes in this population. We propose a broad, theoretically-grounded model of nurse-led interventions for people with multimorbidity, which we intend to use as a basis for our intervention to improve outcomes in people with multimorbidity and palliative conditions.

Reduced methylation corresponds with diabetic nephropathy risk in type 1 diabetes reduced methylation corresponds with diabetic nephropathy risk.

Abstract: Diabetic nephropathy (DN) is a polygenic disorder with few risk variants showing robust replication in large-scale genome-wide association studies. To understand the role of DNA methylation, it is important to have the prevailing genomic view to distinguish key sequence elements that influence gene expression. This is particularly challenging for DN because genome wide methylation patterns are poorly defined. While methylation is known to alter gene expression the importance of this causal relationship is obscured by array-based technologies since coverage outside promoter regions is low. To overcome these challenges, we performed methylation sequencing using leukocytes derived from participants of the Finnish Diabetic Nephropathy (FinnDiane) type 1 diabetes (T1D) study (n=39) that was subsequently replicated in a larger validation cohort (n=296). Gene body related regions made up >60% of the methylation differences and emphasised the importance of methylation sequencing. We observe differentially methylated genes associated with DN (DDN) in three independent T1D registries originating from Denmark (n=445), Hong Kong (n=107) and Thailand (n=130). Reduced DNA methylation at CTCF and Pol2B sites were tightly connected with DN pathways that include insulin signalling, lipid metabolism and fibrosis. To define the pathophysiological significance of these population findings, methylation indices were assessed in human renal cells such as podocytes and proximal convoluted tubules. The expression of core genes was associated with reduced methylation, elevated CTCF and Pol2B binding and the activation of insulin signalling phosphoproteins in hyperglycaemic cells. These experimental observations also closely parallel methylation-mediated regulation in human macrophage and vascular endothelial cells.

100 Multimorbidity and disease-count as predictors of healthcare use and mortality in emergency department attenders: a cross-sectional secondary analysis of routinely-collected data

Abstract:

Background

Having 2 or more chronic conditions (multimorbidity) is associated with increased mortality and healthcare use in community-dwelling populations. In order to develop a nurse-led intervention for people with multimorbidity and palliative conditions, we sought to explore whether multimorbidity and disease-count were significant predictors of mortality and healthcare use in emergency department (ED) attenders.

Methods

We conducted secondary analyses of inpatient and ED records for Glasgow (Scotland) residents attending the ED between April 2019 and March 2020. We conducted binomial logistic regression and calculated adjusted/unadjusted odds ratios (ORs) with 95% confidence intervals (CIs). Age, sex, ethnicity and deprivation were included in adjusted models. To handle missing data, complete case analysis was conducted and compared with results from post-imputation analyses. Ethical approval obtained from Local Public Advisory Committee.

Results

126,158 attendances by 75,726 eligible persons occurred during the study period. Complete data was available for 63,331 persons. Multimorbidity and disease count were significant predictors of all outcomes in both adjusted and unadjusted models. Complete case and post-imputation analyses produced comparable results. Of particular relevance to palliative care, only a small number of individuals died during admission (n=1.031, 1.6%), but multimorbidity was a significant predictor of this in both crude (OR: 4.41, 95% CI: 3.90–5.00) and adjusted (adjusted OR: 1.80, 95% CI: 1.58–2.05) analyses.

Conclusions

Significant associations were detected with access to only 2–3 years historical inpatient data, so further validation of these predictors with greater historic inpatient and primary care data is warranted. We have however shown that these predictors are significant and should be incorporated into models aimed at identifying people at risk of healthcare use and mortality. Improving end-of-life care for people with multimorbidity is an avenue for further research, and robust models which can handle major class imbalances (only 1.6% ED attenders died during admission) should be tested.

Unsupervised classification applications in enhancing lithological mapping and geological understanding – A case study from Northern Ireland

Abstract: Using pattern classification algorithms can help recognise and predict patterns in large and complex multivariate datasets. Utilising competitive learning, self-organising maps (SOMs) are known unsupervised classification tools that are considered very useful in pattern classification and recognition. This technique is based on the principles of vector quantification of similarities and clustering in a high-dimensional space, where the method can handle the analysis and visualization of high-dimensional data. The tool is ideal for analysing a complex combination of categorical and continuous spatial variables, with particular applications to geological features. In this paper, we employ the tool to predict geological features based on airborne geophysical data acquired through the Tellus project in Northern Ireland. SOMs are applied through 8 experiments (iterations), incorporating the radiometric data in combination with geological features, including elevation, slope angle, terrain ruggedness (TRI), and geochronology. The SOMs proved successful in differentiating contrasting bedrock geology, such as acidic versus mafic igneous rocks, while data clustering over intermediate rocks was not as apparent. The presence of a thick cover of glacial deposits in most of the study area presented a challenge in the data clustering, particularly over the intermediate igneous and sedimentary bedrock types. Supplementary material: https://doi.org/10.6084/m9.figshare.c.6603098

Skin 11β-hydroxysteroid dehydrogenase type 1 enzyme expression regulates burn wound healing and can be targeted to modify scar characteristics

Abstract: Abstract Background Excessive scarring and fibrosis are the most severe and common complications of burn injury. Prolonged exposure to high levels of glucocorticoids detrimentally impacts on skin, leading to skin thinning and impaired wound healing. Skin can generate active glucocorticoids locally through expression and activity of the 11β-hydroxysteroid dehydrogenase type 1 enzyme (11β-HSD1). We hypothesised that burn injury would induce 11β-HSD1 expression and local glucocorticoid metabolism, which would have important impacts on wound healing, fibrosis and scarring. We additionally proposed that pharmacological manipulation of this system could improve aspects of post-burn scarring. Methods Skin 11β-HSD1 expression in burns patients and mice was examined. The impacts of 11β-HSD1 mediating glucocorticoid metabolism on burn wound healing, scar formation and scar elasticity and quality were additionally examined using a murine 11β-HSD1 genetic knockout model. Slow-release scaffolds containing therapeutic agents, including active and inactive glucocorticoids, were developed and pre-clinically tested in mice with burn injury. Results We demonstrate that 11β-HSD1 expression levels increased substantially in both human and mouse skin after burn injury. 11β-HSD1 knockout mice experienced faster wound healing than wild type mice but the healed wounds manifested significantly more collagen deposition, tensile strength and stiffness, features characteristic of excessive scarring. Application of slow-release prednisone, an inactive glucocorticoid, slowed the initial rate of wound closure but significantly reduced post-burn scarring via reductions in inflammation, myofibroblast generation, collagen production and scar stiffness. Conclusions Skin 11β-HSD1 expression is a key regulator of wound healing and scarring after burn injury. Application of an inactive glucocorticoid capable of activation by local 11β-HSD1 in skin slows the initial rate of wound closure but significantlyimproves scar characteristics post burn injury.

SGLT2 inhibitors for patients with type 2 diabetes and CKD: a narrative review.

Abstract: Sodium-glucose co-transporter 2 (SGLT2) inhibitors have recently emerged as an effective means to protect kidney function in people with type 2 diabetes and chronic kidney disease (CKD). In this review, we explore the role of SGLT2 inhibition in these individuals. SGLT2 inhibitors specifically act to inhibit sodium and glucose reabsorption in the early proximal tubule of the renal nephron. Although originally developed as glucose-lowering agents through their ability to induce glycosuria, it became apparent in cardiovascular outcome trials that the trajectory of kidney function decline was significantly slowed and the incidence of serious falls in kidney function was reduced in participants receiving an SGLT2 inhibitor. These observations have recently led to specific outcome trials in participants with CKD, including DAPA-CKD, CREDENCE and EMPA-KIDNEY, and real-world studies, like CVD-REAL-3, that have confirmed the observation of kidney benefits in this setting. In response, recent KDIGO Guidelines have recommended the use of SGLT2 inhibitors as first line therapy in patients with CKD, alongside statins, renin-angiotensin-aldosterone system inhibitors and multifactorial risk factor management as indicated. However, SGLT2 inhibitors remain significantly underutilized in the setting of CKD. Indeed, an inertia paradox exists, with patients with more severe disease less likely to receive an SGLT2 inhibitor. Concerns regarding safety appear unfounded, as acute kidney injury, hyperkalaemia, major acute cardiovascular events and cardiac death in patients with CKD appear to be lower following SGLT2 inhibition. The first-in-class indication of dapagliflozin for CKD may begin a new approach to managing kidney disease in type 2 diabetes.

Recycling glucocorticoids: therapeutic implications of the 11β-HSD1 enzyme system.

Abstract: Endogenous glucocorticoids and commonly used oral glucocorticoids have the property of existing in an inactive and active form in vivo. The inactive form can be converted back to the active form, or 'recycled' in cells and tissues that express the 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1) enzyme. This recycling provides an important contribution to the action of glucocorticoids. This review examines the literature relating to the importance of 11β-HSD1 activity during glucocorticoid treatment with an emphasis on studies examining bone and joint disease and the ability of glucocorticoids to suppress inflammatory damage in models of arthritis. Animal models with global or selective deletion of 11β-HSD1 have determined the extent to which this recycling is important in normal physiology and during treatment with oral glucocorticoids. These studies demonstrate that 11β-HSD1 mediated recycling of inactive glucocorticoids has a substantial action and indeed is responsible for the majority of the effects of orally administered glucocorticoids on a range of tissues. Importantly, the anti-inflammatory actions of glucocorticoids appear largely through this mechanism such that mice that lack 11β-HSD1 are resistant to the anti-inflammatory actions of glucocorticoids. The recognition that to a large extent the circulating inactive counterpart of these glucocorticoids is more important to anti-inflammatory effects than the active glucocorticoid presents novel opportunities to more selectively target glucocorticoids to tissues or to reduce the likely side effects.

An Engineered Nanosugar Enables Rapid and Sustained Glucose‐Responsive Insulin Delivery in Diabetic Mice

Abstract: Glucose‐responsive insulin‐delivery platforms that are sensitive to dynamic glucose concentration fluctuations and provide both rapid and prolonged insulin release have great potential to control hyperglycemia and avoid hypoglycemia diabetes. Here, biodegradable and charge‐switchable phytoglycogen nanoparticles capable of glucose‐stimulated insulin release are engineered. The nanoparticles are “nanosugars” bearing glucose‐sensitive phenylboronic acid groups and amine moieties that allow effective complexation with insulin (≈95% loading capacity) to form nanocomplexes. A single subcutaneous injection of nanocomplexes shows a rapid and efficient response to a glucose challenge in two distinct diabetic mouse models, resulting in optimal blood glucose levels (below 200 mg dL–1) for up to 13 h. The morphology of the nanocomplexes is found to be key to controlling rapid and extended glucose‐regulated insulin delivery in vivo. These studies reveal that the injected nanocomplexes enabled efficient insulin release in the mouse, with optimal bioavailability, pharmacokinetics, and safety profiles. These results highlight a promising strategy for the development of a glucose‐responsive insulin delivery system based on a natural and biodegradable nanosugar.