Glycaemic patterns of male professional athletes with type 1 diabetes during exercise, recovery and sleep: Retrospective, observational study over an entire competitive season.

AIMS: To analyse glycaemic patterns of professional athletes with type 1 diabetes during a competitive season. MATERIALS AND METHODS: We analysed continuous glucose monitoring data of 12 professional male cyclists with type 1 diabetes during exercise, recovery and sleep on days with competitive exercise (CE) and non-competitive exercise (NCE). We assessed whether differences exist between CE and NCE days and analysed associations between exercise and dysglycaemia. RESULTS: The mean glycated haemoglobin was 50 ± 5 mmol/mol (6.7 ± 0.5%). The athletes cycled on 280.8 ± 28.1 days (entire season 332.6 ± 18.8 days). Overall, time in range (3.9-10 mmol/L) was 70.0 ± 13.7%, time in hypoglycaemia (<3.9 mmol/L) was 6.4 ± 4.7% and time in hyperglycaemia (>10 mmol/L) was 23.6 ± 12.5%. During the nights of NCE days, athletes spent 10.1 ± 7.4% of time in hypoglycaemia, particularly after exercise in the endurance zones. The CE days were characterized by a higher time in hyperglycaemia compared with NCE days (25.2 ± 12.5% vs. 22.2 ± 12.1%, p = .012). This was driven by the CE phase, where time in range dropped to 60.4 ± 13.0% and time in hyperglycaemia was elevated (38.5 ± 12.9%). Mean glucose was higher during CE compared with NCE sessions (9.6 ± 0.9 mmol/L vs. 7.8 ± 1.1 mmol/L, p < .001). The probability of hyperglycaemia during exercise was particularly increased with longer duration, higher intensity and higher variability of exercise. CONCLUSIONS: The analysis of glycaemic patterns of professional endurance athletes revealed that overall glycaemia was generally within targets. For further improvement, athletes, team staff and caregivers may focus on hyperglycaemia during competitions and nocturnal hypoglycaemia after NCE.

Clinical Considerations and Practical Advice for People Living With Type 2 Diabetes Who Undertake Regular Exercise or Aim to Exercise Competitively.

This article provides practical tips for advising people with type 2 diabetes on how to engage in regular exercise safely and effectively. Its focus is on individuals who wish to exceed the minimum physical activity recommendation of 150 minutes/week of moderate-intensity exercise or even compete in their chosen sport. Health care professionals who work with such individuals must have a basic understanding of glucose metabolism during exercise, nutritional requirements, blood glucose management, medications, and sport-related considerations. This article reviews three key aspects of individualized care for physically active people with type 2 diabetes: 1) initial medical assessment and pre-exercise screenings, 2) glucose monitoring and nutritional considerations, and 3) the combined glycemic effects of exercise and medications.

Rust expression browser: an open source database for simultaneous analysis of host and pathogen gene expression profiles with expVIP.

BACKGROUND: Transcriptomics is being increasingly applied to generate new insight into the interactions between plants and their pathogens. For the wheat yellow (stripe) rust pathogen (Puccinia striiformis f. sp. tritici, Pst) RNA-based sequencing (RNA-Seq) has proved particularly valuable, overcoming the barriers associated with its obligate biotrophic nature. This includes the application of RNA-Seq approaches to study Pst and wheat gene expression dynamics over time and the Pst population composition through the use of a novel RNA-Seq based surveillance approach called "field pathogenomics". As a dual RNA-Seq approach, the field pathogenomics technique also provides gene expression data from the host, giving new insight into host responses. However, this has created a wealth of data for interrogation. RESULTS: Here, we used the field pathogenomics approach to generate 538 new RNA-Seq datasets from Pst-infected field wheat samples, doubling the amount of transcriptomics data available for this important pathosystem. We then analysed these datasets alongside 66 RNA-Seq datasets from four Pst infection time-courses and 420 Pst-infected plant field and laboratory samples that were publicly available. A database of gene expression values for Pst and wheat was generated for each of these 1024 RNA-Seq datasets and incorporated into the development of the rust expression browser ( http://www.rust-expression.com ). This enables for the first time simultaneous 'point-and-click' access to gene expression profiles for Pst and its wheat host and represents the largest database of processed RNA-Seq datasets available for any of the three Puccinia wheat rust pathogens. We also demonstrated the utility of the browser through investigation of expression of putative Pst virulence genes over time and examined the host plants response to Pst infection. CONCLUSIONS: The rust expression browser offers immense value to the wider community, facilitating data sharing and transparency and the underlying database can be continually expanded as more datasets become publicly available.

The effects of training population design on genomic prediction accuracy in wheat.

Genomic selection offers several routes for increasing the genetic gain or efficiency of plant breeding programmes. In various species of livestock, there is empirical evidence of increased rates of genetic gain from the use of genomic selection to target different aspects of the breeder's equation. Accurate predictions of genomic breeding value are central to this, and the design of training sets is in turn central to achieving sufficient levels of accuracy. In summary, small numbers of close relatives and very large numbers of distant relatives are expected to enable predictions with higher accuracy. To quantify the effect of some of the properties of training sets on the accuracy of genomic selection in crops, we performed an extensive field-based winter wheat trial. In summary, this trial involved the construction of 44 F2:4 bi- and tri-parental populations, from which 2992 lines were grown on four field locations and yield was measured. For each line, genotype data were generated for 25 K segregating SNP markers. The overall heritability of yield was estimated to 0.65, and estimates within individual families ranged between 0.10 and 0.85. Genomic prediction accuracies of yield BLUEs were 0.125-0.127 using two different cross-validation approaches and generally increased with training set size. Using related crosses in training and validation sets generally resulted in higher prediction accuracies than using unrelated crosses. The results of this study emphasise the importance of the training panel design in relation to the genetic material to which the resulting prediction model is to be applied.

Collecting wild Miscanthus germplasm in Asia for crop improvement and conservation in Europe whilst adhering to the guidelines of the United Nations' Convention on Biological Diversity.

BACKGROUND AND AIMS: Germplasm with diverse, agronomically relevant traits forms the foundation of a successful plant breeding programme. Since 1993, the United Nations has been advocating the implementation of the Convention on Biological Diversity (CBD) and the subsequent 2002 Bonn Guidelines as international best practice on germplasm collection and use. In 2006, a European team made an expedition to Asia to collect wild germplasm of Miscanthus, a C4 perennial rhizomatous grass, for breeding an environmentally adaptable, resilient and high-yielding bioenergy crop. We outline general aspects of germplasm collection, conservation, breeding and biomass production evaluation while following the CBD's guidelines, respecting biodiversity and conservation needs, and the ethical use of genetic resources. METHODS: Effective protocols, quarantine, methods for collecting seed and rhizomes, and a genebank for conservation were established. Versatile informatics and database architecture were used to assist in selection, flowering synchronization, crossing, evaluation, phenotyping and data integration. Approaches were formulated to comply with the CBD guidelines. KEY RESULTS: A total of 303 accessions of M. sinensis, M. sacchariflorus and M. floridulus were collected from 158 geographically and environmentally diverse locations. These species were shown to accumulate different amounts of aerial biomass due to combinations of stem count, height and thickness. Progeny from one interspecies cross accumulated more biomass in early trials and has shown double the yield performance in years 3-4 compared with the existing commercial cultivar M. × giganteus. An example of an F1 hybrid has already demonstrated the long-term potential of exploiting this collection for a breeding programme. CONCLUSIONS: By conforming to the CBD principles, the authors' international collaboration provides a practical example of implementing the CBD. The collection widened the genetic diversity of Miscanthus available to allow for breeding of novel hybrids that exhibit more diverse traits to increase yield and resilience for growth on marginal land and in climate-challenged environments.

Phenomic and genomic prediction of yield on multiple locations in winter wheat.

Genomic selection has recently become an established part of breeding strategies in cereals. However, a limitation of linear genomic prediction models for complex traits such as yield is that these are unable to accommodate Genotype by Environment effects, which are commonly observed over trials on multiple locations. In this study, we investigated how this environmental variation can be captured by the collection of a large number of phenomic markers using high-throughput field phenotyping and whether it can increase GS prediction accuracy. For this purpose, 44 winter wheat (Triticum aestivum L.) elite populations, comprising 2,994 lines, were grown on two sites over 2 years, to approximate the size of trials in a practical breeding programme. At various growth stages, remote sensing data from multi- and hyperspectral cameras, as well as traditional ground-based visual crop assessment scores, were collected with approximately 100 different data variables collected per plot. The predictive power for grain yield was tested for the various data types, with or without genome-wide marker data sets. Models using phenomic traits alone had a greater predictive value (R2 = 0.39-0.47) than genomic data (approximately R2 = 0.1). The average improvement in predictive power by combining trait and marker data was 6%-12% over the best phenomic-only model, and performed best when data from one full location was used to predict the yield on an entire second location. The results suggest that genetic gain in breeding programmes can be increased by utilisation of large numbers of phenotypic variables using remote sensing in field trials, although at what stage of the breeding cycle phenomic selection could be most profitably applied remains to be answered.

Evaluation of Factors Related to Glycemic Management in Professional Cyclists With Type 1 Diabetes Over a 7-Day Stage Race.

OBJECTIVE: To investigate factors related to glycemic management among members of a professional cycling team with type 1 diabetes over a 7-day Union Cycliste Internationale World Tour stage race. RESEARCH DESIGN AND METHODS: An observational evaluation of possible factors related to glycemic management and performance in six male professional cyclists with type 1 diabetes (HbA1c 6.4 ± 0.6%) during the 2019 Tour of California. RESULTS: In-ride time spent in euglycemia (3.9-10.0 mmol/L glucose) was 63 ± 11%, with a low percentage of time spent in level 1 (3.0-3.9 mmol/L; 0 ± 1% of time) and level 2 (<3.0 mmol/L; 0 ± 0% of time) hypoglycemia over the 7-day race. Riders spent 25 ± 9% of time in level 1 (10.1-13.9 mmol/L) and 11 ± 9% in level 2 (>13.9 mmol/L) hyperglycemia during races. Bolus insulin use was uncommon during races, despite high carbohydrate intake (76 ± 23 g ⋅ h-1). Overnight, the riders spent progressively more time in hypoglycemia from day 1 (6 ± 12% in level 1 and 0 ± 0% in level 2) to day 7 (12 ± 12% in level 1 and 2 ± 4% in level 2) (χ2[1] > 4.78, P < 0.05). CONCLUSIONS: Professional cyclists with type 1 diabetes have excellent in-race glycemia, but significant hypoglycemia during recovery overnight, throughout a 7-day stage race.

Glycemic responses to strenuous training in male professional cyclists with type 1 diabetes: a prospective observational study.

INTRODUCTION: This prospective observational study sought to establish the glycemic, physiological and dietary demands of strenuous exercise training as part of a 9-day performance camp in a professional cycling team with type 1 diabetes (T1D). RESEARCH DESIGN AND METHODS: Sixteen male professional cyclists with T1D on multiple daily injections (age: 27±4 years; duration of T1D: 11±5 years; body mass index: 22±2 kg/m2; glycated hemoglobin: 7%±1% (50±6 mmol/mol); maximum rate of oxygen consumption: 73±4 mL/kg/min) performed road cycle sessions (50%-90% of the anaerobic threshold, duration 1-6 hours) over 9 consecutive days. Glycemic (Dexcom G6), nutrition and physiological data were collected throughout. Glycemic data were stratified into predefined glycemic ranges and mapped alongside exercise physiology and nutritional parameters, as well as split into daytime and night-time phases for comparative analysis. Data were assessed by means of analysis of variance and paired t-tests. A p value of ≤0.05 (two-tailed) was statistically significant. RESULTS: Higher levels of antecedent hypoglycemia in the nocturnal hours were associated with greater time spent in next-day hypoglycemia overall (p=0.003) and during exercise (p=0.019). Occurrence of nocturnal hypoglycemia was associated with over three times the risk of next-day hypoglycemia (p<0.001) and a twofold risk of low glucose during cycling (p<0.001). Moreover, there was trend for a greater amount of time spent in mild hypoglycemia during the night compared with daytime hours (p=0.080). CONCLUSION: The higher prevalence of nocturnal hypoglycemia was associated with an increased risk of next-day hypoglycemia, which extended to cycle training sessions. These data highlight the potential need for additional prebed carbohydrates and/or insulin dose reduction strategies around exercise training in professional cyclists with T1D. TRIAL REGISTRATION NUMBER: DRKS00019923.

Role of physical activity in diabetes management and prevention.

During recent years, evidence supporting the vital role of physical activity in the prevention and treatment of diabetes has been accumulating. Physical activity is recognized to produce multiple general and diabetes-specific health benefits. Yet despite the multitude of benefits, many people are physically inactive. As the prevalence of overweight and obesity, prediabetes, and type 2 diabetes has continued to rise at an alarming rate, physical inactivity has become an urgent public health concern. The purpose of this article is to review the physical activity/exercise research in diabetes and summarize the current exercise recommendations. This information can be used by clinicians to make safe and effective recommendations for integrating physical activity/exercise into self-management plans for individuals with diabetes or at risk for its development.

Comparison of environmental fate and transport process descriptors of explosives in saline and freshwater systems.

Environmental process descriptors are necessary to evaluate the fate and transport of munitions constituents that have been introduced into the environment. An extensive database exists for freshwater environments; however, explosives fate and transport parameters such as dissolution rates, transformation rates, and adsorption of explosives have not been evaluated under both freshwater and saline conditions to determine the applicability of the freshwater data to saline environments. The objective of this study was to determine if freshwater fate and transport processes were similar to those determined under saline water conditions. We evaluated TNT, RDX, and HMX dissolution rates, transformation rates, and adsorption under freshwater and saline conditions in batch tests. Results showed a generally close agreement. Therefore, the existing freshwater database for explosives fate and transport process descriptors can be used in marine environments.

TNT particle size distributions from detonated 155-mm howitzer rounds.

To achieve sustainable range management and avoid or minimize environmental contamination, the Army needs to know the amount of explosives deposited on ranges from different munitions and how these are degraded and transported under different geological and climatic conditions. The physical form of the deposited explosives has a bearing on this problem, yet the shapes and size distributions of the explosive particles remaining after detonations are not known. We collected residues from 8 high-order and 6 low-order non-tactical detonations of TNT-filled 155-mm rounds. We found significant variation in the amount of TNT scattered from the high-order detonations, ranging from 0.00001 to 2% of the TNT in the original shell. All low-order detonations scattered percent-level amounts of TNT. We imaged thousands of TNT particles and determined the size, mass and surface-area distributions of particles collected from one high-order and one low-order detonation. For the high-order detonation, particles smaller than 1 mm contribute most of the mass and surface area of the TNT scattered. For the low-order detonation, most of the scattered TNT mass was in the form of un-heated, centimeter-sized pieces whereas most of the surface area was again from particles smaller than 1 mm. We also observed that the large pieces of TNT disintegrate readily, giving rise to many smaller particles that can quickly dissolve. We suggest picking up the large pieces of TNT before they disintegrate to become point sources of contamination.