Exercise for the Prevention of Anthracycline-Induced Functional Disability and Cardiac Dysfunction: The BREXIT Study.

BACKGROUND: Breast cancer survivors treated with anthracycline-based chemotherapy (AC) have increased risk of functional limitation and cardiac dysfunction. We conducted a 12-month randomized controlled trial in 104 patients with early-stage breast cancer scheduled for AC to determine whether 12 months of exercise training (ExT) could attenuate functional disability (primary end point), improve cardiorespiratory fitness (VO2peak), and prevent cardiac dysfunction. METHODS: Women 40 to 75 years of age with stage I to III breast cancer scheduled for AC were randomized to 3 to 4 days per week aerobic and resistance ExT for 12 months (n=52) or usual care (UC; n=52). Functional measures were performed at baseline, at 4 weeks after AC (4 months), and at 12 months, comprising: (1) cardiopulmonary exercise testing to quantify VO2peak and functional disability (VO2peak ≤18.0 mL·kg-1·min-1); (2) cardiac reserve (response from rest to peak exercise), quantified with exercise cardiac magnetic resonance measures to determine changes in left and right ventricular ejection fraction, cardiac output, and stroke volume; (3) standard-of-care echocardiography-derived resting left ventricular ejection fraction and global longitudinal strain; and (4) biochemistry (troponin and BNP [B-type natriuretic peptide]). RESULTS: Among 104 participants randomized, greater study attrition was observed among UC participants (P=0.031), with 93 women assessed at 4 months (ExT, n=49; UC, n=44) and 87 women assessed at 12 months (ExT, n=49; UC, n=38). ExT attenuated functional disability at 4 months (odds ratio, 0.32 [95% CI, 0.11-0.94]; P=0.03) but not at 12 months (odds ratio, 0.27 [95% CI, 0.06-1.12]; P=0.07). In a per-protocol analysis, functional disability was prevented entirely at 12 months among participants adherent to ExT (ExT, 0% versus UC, 20%; P=0.005). Compared with UC at 12 months, ExT was associated with a net 3.5-mL·kg-1·min-1 improvement in VO2peak that coincided with greater cardiac output, stroke volume, and left and right ventricular ejection fraction reserve (P<0.001 for all). There was no effect of ExT on resting measures of left ventricular function. Postchemotherapy troponin increased less in ExT than in UC (8-fold versus 16-fold increase; P=0.002). There were no changes in BNP in either group. CONCLUSIONS: In women with early-stage breast cancer undergoing AC, 12 months of ExT did not attenuate functional disability, but provided large, clinically meaningful benefits on VO2peak and cardiac reserve. REGISTRATION: URL: https://www.anzctr.org.au/; Unique identifier: ACTRN12617001408370.

Urine Albumin-Creatinine Ratio Variability in People With Type 2 Diabetes: Clinical and Research Implications.

RATIONALE & OBJECTIVE: Evidence has demonstrated that albuminuria is a key diagnostic and prognostic marker of diabetic chronic kidney disease, but the impact of its day-to-day variability has not been adequately considered. This study quantified within-individual variability of albuminuria in people with type 2 diabetes to inform clinical albuminuria monitoring. STUDY DESIGN: Descriptive cross-sectional analysis. SETTING & PARTICIPANTS: People with type 2 diabetes (n=826, 67.1 [IQR, 60.3-72.4] years, 64.9% male) participating in the Progression of Diabetic Complications (PREDICT) cohort study. EXPOSURE: Four spot urine collections for measurement of urinary albumin-creatinine ratio (UACR) within 4 weeks. OUTCOME: Variability of UACR. ANALYTICAL APPROACH: We characterized within-individual variability (coefficient of variation [CV], 95% limits of random variation, intraclass correlation coefficient), developed a calculator displaying probabilities that any observed difference between a pair of UACR values truly exceeded a 30% difference, and estimated the ranges of diagnostic uncertainty to inform a need for additional UACR collections to exclude or confirm albuminuria. Multiple linear regression examined factors influencing UACR variability. RESULTS: We observed high within-individual variability (CV 48.8%; 95% limits of random variation showed a repeated UACR to be as high/low as 3.78/0.26 times the first). If a single-collection UACR increased from 2 to 5mg/mmol, the probability that UACR actually increased by at least 30% was only 50%, rising to 97% when 2 collections were obtained at each time point. The ranges of diagnostic uncertainty were 2.0-4.0mg/mmol after an initial UACR test, narrowing to 2.4-3.2 and 2.7-2.9mg/mmol for the mean of 2 and 3 collections, respectively. Some factors correlated with higher (female sex; moderately increased albuminuria) or lower (reduced estimated glomerular filtration rate and sodium-glucose cotransporter 2 inhibitor/angiotensin-converting enzyme inhibitor/angiotensin receptor blocker treatment) within-individual UACR variability. LIMITATIONS: Reliance on the mean of 4 UACR collections as the reference standard for albuminuria. CONCLUSIONS: UACR demonstrates a high degree of within-individual variability among individuals with type 2 diabetes. Multiple urine collections for UACR may improve capacity to monitor changes over time in clinical and research settings but may not be necessary for the diagnosis of albuminuria. PLAIN-LANGUAGE SUMMARY: Albuminuria (albumin in urine) is a diagnostic and prognostic marker of diabetic chronic kidney disease. However, albuminuria can vary within an individual from day to day. We compared 4 random spot urinary albumin-creatinine ratio (UACR) samples from 826 participants. We found that a second UACR collection may be as small as a fourth or as large as almost 4 times the first sample's UACR level. This high degree of variability presents a challenge to our ability to interpret changes in albuminuria. Multiple collections have been suggested as a solution. We have constructed tools that may aid clinicians in deciding how many urine collections are required to monitor and diagnose albuminuria. Multiple urine collections may be required for individual monitoring but not necessarily for diagnosis.

Liver disease mortality and hospitalisations among people with type 2 diabetes mellitus: A population-based study.

BACKGROUND AND AIMS: The burden of liver disease among people with diabetes at a population level is unknown. We explored the burden and trends of liver disease mortality and hospitalisations among Australians with diabetes. METHODS: We linked Australians with type 2 diabetes on the National Diabetes Services Scheme to the National Death Index for 2002-2019 to determine trends in the proportion of deaths due to liver disease, overall and by subcategory. We also determined the leading reasons and risk factors for liver disease hospitalisations in those with diabetes over this period. Finally, we compared the burden of liver disease hospitalisations among those with diabetes to the general population using excess hospitalisations per 100 000 person-years. RESULTS: Among Australians with type 2 diabetes (n = 1 122 431) liver diseases accounted for between 1.5% and 1.9% of deaths between 2002 and 2019, roughly one-third of the proportion of deaths caused by kidney disease. The proportion of deaths due to inflammatory liver diseases among those with diabetes increased from .08% in 2002 to .27% in 2019. Alcohol-related liver disease accounted for the greatest share (22.7%) of liver disease hospitalisation in those with diabetes, but the number of hospitalisations for this condition declined over time. Compared to the general population, men (RR 3.63, 95% CI 3.44-3.84) and women (RR 4.49, 4.21-4.78) with diabetes were at higher risk of hospitalisation for fibrosis and cirrhosis; however, this did not translate to a substantial excess risk per 100 000 population. CONCLUSIONS: Better screening methods for liver disease among people with diabetes should be developed and implemented into practice.

Detection of sedentary time and bouts using consumer-grade wrist-worn devices: a hidden semi-Markov model.

BACKGROUND: Wrist-worn data from commercially available devices has potential to characterize sedentary time for research and for clinical and public health applications. We propose a model that utilizes heart rate in addition to step count data to estimate the proportion of time spent being sedentary and the usual length of sedentary bouts. METHODS: We developed and trained two Hidden semi-Markov models, STEPHEN (STEP and Heart ENcoder) and STEPCODE (STEP enCODEr; a steps-only based model) using consumer-grade Fitbit device data from participants under free living conditions, and validated model performance using two external datasets. We used the median absolute percentage error (MDAPE) to measure the accuracy of the proposed models against research-grade activPAL device data as the referent. Bland-Altman plots summarized the individual-level agreement with activPAL. RESULTS: In OPTIMISE cohort, STEPHEN's estimates of the proportion of time spent sedentary had significantly (p < 0.001) better accuracy (MDAPE [IQR] = 0.15 [0.06-0.25] vs. 0.23 [0.13-0.53)]) and agreement (Bias Mean [SD]=-0.03[0.11] vs. 0.14 [0.11]) than the proprietary software, estimated the usual sedentary bout duration more accurately (MDAPE[IQR] = 0.11[0.06-0.26] vs. 0.42[0.32-0.48]), and had better agreement (Bias Mean [SD] = 3.91[5.67] minutes vs. -11.93[5.07] minutes). With the ALLO-Active dataset, STEPHEN and STEPCODE did not improve the estimation of proportion of time spent sedentary, but STEPHEN estimated usual sedentary bout duration more accurately than the proprietary software (MDAPE[IQR] = 0.19[0.03-0.25] vs. 0.36[0.15-0.48]) and had smaller bias (Bias Mean[SD] = 0.70[8.89] minutes vs. -11.35[9.17] minutes). CONCLUSIONS: STEPHEN can characterize the proportion of time spent being sedentary and usual sedentary bout length. The methodology is available as an open access R package available from https://github.com/limfuxing/stephen/ . The package includes trained models, but users have the flexibility to train their own models.

Changes in the incidence of type 2 diabetes in Australia, 2005-2019, overall and by socio-demographic characteristics: a population-based study.

OBJECTIVES: To estimate changes in the incidence of clinically diagnosed type 2 diabetes in Australia, overall and by age, sex, socio-economic disadvantage, geographic remoteness, and country of birth. STUDY DESIGN: Population-based study; analysis of National Diabetes Services Scheme (NDSS) data (age-period-cohort models). SETTING, PARTICIPANTS: Data were extracted for incident cases of type 2 diabetes, 1 January 2005 to 31 December 2019, in residents of the Australian Capital Territory, New South Wales, Queensland, and Victoria aged 20 years or older registered with the NDSS. The numbers of people at risk were obtained from the Australian Bureau of Statistics. MAIN OUTCOME MEASURES: Changes in the incidence of type 2 diabetes, 2005-2019, by age, postcode-level socio-economic disadvantage (Index of Relative Socioeconomic Disadvantage) and remoteness (major city, inner regional, outer regional/remote/very remote), and country of birth, stratified by sex. RESULTS: During 2005-2019, 741 535 people aged 20 years or older with incident type 2 diabetes were registered with the NDSS; 421 190 were men (56.8%). Overall, the incidence of type 2 diabetes increased with age (until about age 70 years) and socio-economic disadvantage for both sexes; it was higher in inner regional areas than in major cities or outer regional/remote/very remote areas during 2005-2015, but highest among people in major cities after 2015. The age-standardised incidence of type 2 diabetes increased during 2005-2010, both among men (annual percentage change [APC], 4.4%; 95% confidence interval [CI], 3.6-5.2%) and women (APC, 2.9%; 95% CI, 2.2-3.7%); it declined during 2010-2019 among both men (APC, -5.2%; 95% CI, -5.4% to -4.9%) and women (APC, -6.5%; 95% CI, -6.8% to -6.2%). In general, similar patterns (but of differing magnitude) applied to all age, sex, socio-economic disadvantage, and remoteness groups. However, the incidence of type 2 diabetes increased during 2011-2019 among people born in Asia, North Africa and the Middle East, and the Pacific Islands. CONCLUSIONS: The incidence of type 2 diabetes in Australian adults declined during 2010-2019 across all age, sex, socio-economic disadvantage, and remoteness groups, but increased among people from Asia, North Africa and the Middle East, and the Pacific Islands.

RUV-III-NB: normalization of single cell RNA-seq data.

Normalization of single cell RNA-seq data remains a challenging task. The performance of different methods can vary greatly between datasets when unwanted factors and biology are associated. Most normalization methods also only remove the effects of unwanted variation for the cell embedding but not from gene-level data typically used for differential expression (DE) analysis to identify marker genes. We propose RUV-III-NB, a method that can be used to remove unwanted variation from both the cell embedding and gene-level counts. Using pseudo-replicates, RUV-III-NB explicitly takes into account potential association with biology when removing unwanted variation. The method can be used for both UMI or read counts and returns adjusted counts that can be used for downstream analyses such as clustering, DE and pseudotime analyses. Using published datasets with different technological platforms, kinds of biology and levels of association between biology and unwanted variation, we show that RUV-III-NB manages to remove library size and batch effects, strengthen biological signals, improve DE analyses, and lead to results exhibiting greater concordance with independent datasets of the same kind. The performance of RUV-III-NB is consistent and is not sensitive to the number of factors assumed to contribute to the unwanted variation.

Mortality trends in type 1 diabetes: a multicountry analysis of six population-based cohorts.

AIMS/HYPOTHESIS: Mortality has declined in people with type 1 diabetes in recent decades. We examined how the pattern of decline differs by country, age and sex, and how mortality trends in type 1 diabetes relate to trends in general population mortality. METHODS: We assembled aggregate data on all-cause mortality during the period 2000-2016 in people with type 1 diabetes aged 0-79 years from Australia, Denmark, Latvia, Scotland, Spain (Catalonia) and the USA (Kaiser Permanente Northwest). Data were obtained from administrative sources, health insurance records and registries. All-cause mortality rates in people with type 1 diabetes, and standardised mortality ratios (SMRs) comparing type 1 diabetes with the non-diabetic population, were modelled using Poisson regression, with age and calendar time as quantitative variables, describing the effects using restricted cubic splines with six knots for age and calendar time. Mortality rates were standardised to the age distribution of the aggregate population with type 1 diabetes. RESULTS: All six data sources showed a decline in age- and sex-standardised all-cause mortality rates in people with type 1 diabetes from 2000 to 2016 (or a subset thereof), with annual changes in mortality rates ranging from -2.1% (95% CI -2.8%, -1.3%) to -5.8% (95% CI -6.5%, -5.1%). All-cause mortality was higher for male individuals and for older individuals, but the rate of decline in mortality was generally unaffected by sex or age. SMR was higher in female individuals than male individuals, and appeared to peak at ages 40-70 years. SMR declined over time in Denmark, Scotland and Spain, while remaining stable in the other three data sources. CONCLUSIONS/INTERPRETATION: All-cause mortality in people with type 1 diabetes has declined in recent years in most included populations, but improvements in mortality relative to the non-diabetic population are less consistent.

Accessory subunits are integral for assembly and function of human mitochondrial complex I.

Complex I (NADH:ubiquinone oxidoreductase) is the first enzyme of the mitochondrial respiratory chain and is composed of 45 subunits in humans, making it one of the largest known multi-subunit membrane protein complexes. Complex I exists in supercomplex forms with respiratory chain complexes III and IV, which are together required for the generation of a transmembrane proton gradient used for the synthesis of ATP. Complex I is also a major source of damaging reactive oxygen species and its dysfunction is associated with mitochondrial disease, Parkinson's disease and ageing. Bacterial and human complex I share 14 core subunits that are essential for enzymatic function; however, the role and necessity of the remaining 31 human accessory subunits is unclear. The incorporation of accessory subunits into the complex increases the cellular energetic cost and has necessitated the involvement of numerous assembly factors for complex I biogenesis. Here we use gene editing to generate human knockout cell lines for each accessory subunit. We show that 25 subunits are strictly required for assembly of a functional complex and 1 subunit is essential for cell viability. Quantitative proteomic analysis of cell lines revealed that loss of each subunit affects the stability of other subunits residing in the same structural module. Analysis of proteomic changes after the loss of specific modules revealed that ATP5SL and DMAC1 are required for assembly of the distal portion of the complex I membrane arm. Our results demonstrate the broad importance of accessory subunits in the structure and function of human complex I. Coupling gene-editing technology with proteomics represents a powerful tool for dissecting large multi-subunit complexes and enables the study of complex dysfunction at a cellular level.

Television-viewing time and bodily pain in Australian adults with and without type 2 diabetes: 12-year prospective relationships.

BACKGROUND: Bodily pain is a common presentation in several chronic diseases, yet the influence of sedentary behaviour, common in ageing adults, is unclear. Television-viewing (TV) time is a ubiquitous leisure-time sedentary behaviour, with a potential contribution to the development of bodily pain. We examined bodily pain trajectories and the longitudinal relationships of TV time with the bodily pain severity; and further, the potential moderation of the relationships by type 2 diabetes (T2D) status. METHOD: Data were from 4099 participants (aged 35 to 65 years at baseline) in the Australian Diabetes, Obesity and Lifestyle Study (AusDiab), who took part in the follow-ups at 5 years, 12 years, or both. Bodily pain (from SF36 questionnaire: a 0 to 100 scale, where lower scores indicate more-severe pain), TV time, and T2D status [normal glucose metabolism (NGM), prediabetes, and T2D] were assessed at all three time points. Multilevel growth curve modelling used age (centred at 50 years) as the time metric, adjusting for potential confounders, including physical activity and waist circumference. RESULTS: Mean TV time increased, and bodily pain worsened (i.e., mean bodily pain score decreased) across the three time points. Those with T2D had higher TV time and more-severe bodily pain than those without T2D at all time points. In a fully adjusted model, the mean bodily pain score for those aged 50 years at baseline was 76.9(SE: 2.2) and worsened (i.e., bodily pain score decreased) significantly by 0.3(SE: 0.03) units every additional year (p <0.001). Those with initially more-severe pain had a higher rate of increase in pain severity. At any given time point, a one-hour increase in daily TV time was significantly associated with an increase in pain severity [bodily pain score decreased by 0.69 (SE: 0.17) units each additional hour; p <0.001], accounting for the growth factor (age) and confounders' effects. The association was more-pronounced in those with T2D than in those without (prediabetes or NGM), with the effect of T2D on bodily pain severity becoming more apparent as TV time increases, significantly so when TV time increased above 2.5 hours per day. CONCLUSION: Bodily pain severity increased with age in middle-aged and older Australian adults over a 12-year period, and increments in TV time predicted increased bodily pain severity at any given period, which was more pronounced in those with T2D. While increasing physical activity is a mainstay of the prevention and management of chronic health problems, these new findings highlight the potential of reducing sedentary behaviours in this context.

Associations between grass pollen exposures in utero and in early life with food allergy in 12-month-old infants.

Birth during pollen seasons may influence food allergy risk but no study has assessed pollen exposure. Using the HealthNuts population-based cohort of 5276 infants, we assessed grass pollen exposures, in utero and up to the first 6 months of life, on hen's egg, sesame and peanut allergy outcomes at 12 months. Cumulative pollen exposure in the first 7 days of life increased risk of peanut sensitization aMOR (adjusted multinomial odds ratio) = 1.21 (95% CI: 1.01-1.44). Exposure between first 4-6 months of life increased risk of hen's egg aMOR = 1.02 (95% CI: 1.004-1.04) and sensitization to all foods aMOR = 1.02 (95% CI: 1.003-1.04). Grass pollen exposure was associated with food challenge diagnosed food allergy, but only among infants with a maternal history of food allergy. Exposure to grass pollen in the intrauterine period and infancy may be important but more studies are needed to replicate these findings.

Transcatheter Aortic Valve Implantation Represents an Anti-Inflammatory Therapy Via Reduction of Shear Stress-Induced, Piezo-1-Mediated Monocyte Activation.

BACKGROUND: Aortic valve stenosis is an increasingly prevalent degenerative and inflammatory disease. Transcatheter aortic valve implantation (TAVI) has revolutionized its treatment, thereby avoiding its life-threatening/disabling consequences. Whether aortic valve stenosis is accelerated by inflammation and whether it is itself a cause of inflammation are unclear. We hypothesized that the large shear forces exerted on circulating cells, particularly on the largest circulating cells, monocytes, while passing through stenotic aortic valves result in proinflammatory effects that are resolved with TAVI. METHODS: TAVI provides a unique opportunity to compare the activation status of monocytes under high shear stress (before TAVI) and under low shear stress (after TAVI). The activation status of monocytes was determined with a single-chain antibody, MAN-1, which is specific for the activated ß2-integrin Mac-1. Monocyte function was further characterized by the adhesion of myocytes to stimulated endothelial cells, phagocytic activity, uptake of oxidized low-density lipoprotein, and cytokine expression. In addition, we designed a microfluidic system to recapitulate the shear rate conditions before and after TAVI. We used this tool in combination with functional assays, Ca2+ imaging, siRNA gene silencing, and pharmacological agonists and antagonists to identify the key mechanoreceptor mediating the shear stress sensitivity of monocytes. Last, we stained for monocytes in explanted stenotic aortic human valves. RESULTS: The resolution of high shear stress through TAVI reduces Mac-1 activation, cellular adhesion, phagocytosis, oxidized low-density lipoprotein uptake, and expression of inflammatory markers in monocytes and plasma. Using microfluidics and pharmacological and genetic studies, we could recapitulate high shear stress effects on isolated human monocytes under highly controlled conditions, showing that shear stress-dependent calcium influx and monocyte adhesion are mediated by the mechanosensitive ion channel Piezo-1. We also demonstrate that the expression of this receptor is shear stress dependent and downregulated in patients receiving TAVI. Last, we show monocyte accumulation at the aortic side of leaflets of explanted aortic valves. CONCLUSIONS: We demonstrate that high shear stress, as present in patients with aortic valve stenosis, activates multiple monocyte functions, and we identify Piezo-1 as the mainly responsible mechanoreceptor, representing a potentially druggable target. We demonstrate an anti-inflammatory effect and therefore a novel therapeutic benefit of TAVI.

scClassify: sample size estimation and multiscale classification of cells using single and multiple reference.

Automated cell type identification is a key computational challenge in single-cell RNA-sequencing (scRNA-seq) data. To capitalise on the large collection of well-annotated scRNA-seq datasets, we developed scClassify, a multiscale classification framework based on ensemble learning and cell type hierarchies constructed from single or multiple annotated datasets as references. scClassify enables the estimation of sample size required for accurate classification of cell types in a cell type hierarchy and allows joint classification of cells when multiple references are available. We show that scClassify consistently performs better than other supervised cell type classification methods across 114 pairs of reference and testing data, representing a diverse combination of sizes, technologies and levels of complexity, and further demonstrate the unique components of scClassify through simulations and compendia of experimental datasets. Finally, we demonstrate the scalability of scClassify on large single-cell atlases and highlight a novel application of identifying subpopulations of cells from the Tabula Muris data that were unidentified in the original publication. Together, scClassify represents state-of-the-art methodology in automated cell type identification from scRNA-seq data.

Impact of the COVID-19 pandemic and lockdown restrictions on psychosocial and behavioural outcomes among Australian adults with type 2 diabetes: Findings from the PREDICT cohort study.

AIM: To examine psychosocial and behavioural impacts of the novel coronavirus disease 2019 (COVID-19) pandemic and lockdown restrictions among adults with type 2 diabetes. METHODS: Participants enrolled in the PRogrEssion of DIabetic ComplicaTions (PREDICT) cohort study in Melbourne, Australia (n = 489 with a baseline assessment pre-2020) were invited to complete a phone/online follow-up assessment in mid-2020 (i.e., amidst COVID-19 lockdown restrictions). Repeated assessments that were compared with pre-COVID-19 baseline levels included anxiety symptoms (7-item Generalised Anxiety Disorder scale [GAD-7]), depressive symptoms (8-item Patient Health Questionnaire [PHQ-8]), diabetes distress (Problem Areas in Diabetes scale [PAID]), physical activity/sedentary behaviour, alcohol consumption and diabetes self-management behaviours. Additional once-off measures at follow-up included COVID-19-specific worry, quality of life (QoL), and healthcare appointment changes (telehealth engagement and appointment cancellations/avoidance). RESULTS: Among 470 respondents (96%; aged 66 ± 9 years, 69% men), at least 'moderate' worry about COVID-19 infection was reported by 31%, and 29%-73% reported negative impacts on QoL dimensions (greatest for: leisure activities, feelings about the future, emotional well-being). Younger participants reported more negative impacts (p < 0.05). Overall, anxiety/depressive symptoms were similar at follow-up compared with pre-COVID-19, but diabetes distress reduced (p < 0.001). Worse trajectories of anxiety/depressive symptoms were observed among those who reported COVID-19-specific worry or negative QoL impacts (p < 0.05). Physical activity trended lower (~10%), but sitting time, alcohol consumption and glucose-monitoring frequency remained unchanged. 73% of participants used telehealth, but 43% cancelled a healthcare appointment and 39% avoided new appointments despite perceived need. CONCLUSIONS: COVID-19 lockdown restrictions negatively impacted QoL, some behavioural risk factors and healthcare utilisation in adults with type 2 diabetes. However, generalised anxiety and depressive symptoms remained relatively stable.

Contrasting compositions of sitting, standing, stepping, and sleeping time: associations with glycaemic outcome by diabetes risk.

BACKGROUND: Recent evidence suggests that prolonged sitting and its adverse impact on glycaemic indicators appear to be proportional to the degree of insulin resistance. To investigate this finding in a free-living context, we aimed to examine associations of device-measured 24-h time-use compositions of sitting, standing, stepping, and sleeping with fasting glucose (FPG) and 2 h post-load glucose (2hPLG) levels, and to examine separately the associations with time-use compositions among those at lower and at higher risk of developing type 2 diabetes. METHODS: Cross-sectional analyses examined thigh-worn inclinometer data (activPAL, 7 day, 24 h/day protocol) from 648 participants (aged 36-80 years) at either lower (< 39 mmol/mol; < 5.7% HbA1c) or higher (≥39 mmol/mol; ≥5.7% HbA1c) diabetes risk from the 2011-2012 Australian Diabetes, Obesity and Lifestyle study. Multiple linear regression models were used to examine associations of differing compositions with FPG and 2hPLG, with time spent in each behaviour allowed to vary up to 60 min. RESULTS: In general, the associations with the FPG within the time-use compositions were small, with statistically significant associations observed for sitting and sleeping (in the lower diabetes risk group) and standing (in higher diabetes risk group) only. For 2hPLG, statistically significant associations were observed for stepping only, with findings similar between lower (ß = - 0.12 95%CI:-0.22, - 0.02) and higher (ß = - 0.13 95%CI:-0.26, - 0.01) risk groups. Varying the composition had minimal impact on FPG; however 1 h less sitting time and equivalent increase in standing time was associated with attenuated FPG levels in higher risk only (Δ FPG% = - 1.5 95%CI: - 2.4, - 0.5). Large differences in 2hPLG were observed for both groups when varying the composition. One hour less sitting with equivalent increase in stepping was associated with attenuated 2hPLG, with estimations similar in lower (Δ 2hPLG% = - 3.8 95%CI: - 7.3, - 0.2) and higher (Δ 2hPLG% = - 5.0 95%CI: - 9.7, - 0.0) risk for diabetes. CONCLUSIONS: In middle-aged and older adults, glycaemic control could be improved by reducing daily sitting time and replacing it with stepping. Standing could also be beneficial for those at higher risk of developing type 2 diabetes.

Youth Vascular Consortium (YVC) Protocol: Establishing Reference Intervals for Vascular Ageing in Children, Adolescents and Young Adults.

BACKGROUND: In the last two decades, the global prevalence of paediatric hypertension increased by approximately 75%. Nearly 25% of children are now classified as obese or overweight. Substantial evidence suggests that risk factors for cardiovascular disease (CVD) begin to develop in childhood, thus warranting the need for tools to better screen for early CVD risk in youth. Vascular ageing, the deterioration of vascular structure and function, may be a potentially useful tool for detecting the early and asymptomatic signs of CVD burden. However, it is currently unclear what differentiates normal from pathological ageing in youth as existing reference values for vascular ageing in youth are limited by small sample size or homogenous populations. The international Youth Vascular Consortium (YVC) has been established to address these issues. AIMS: The primary aim of the YVC is to develop reference intervals of normal vascular ageing in children, adolescents, and young adults. The secondary, exploratory, aim is to perform head-to-head comparisons of vascular ageing biomarkers to determine which biomarker is most strongly related to cardiometabolic health. STUDY DESIGN: The YVC is a retrospective, multicentre study and will collate data on vascular ageing in children (5-12 years), adolescents (13-18 years) and young adults (19-40 years), as well as routine clinical biochemistry, lifestyle, sociodemographic factors and parental health. CONCLUSION: To date, 31 research groups from 19 countries have joined the YVC. To our knowledge, this will be the largest study of its kind to investigate vascular ageing in youth.

A systematic review of trends in all-cause mortality among people with diabetes.

AIMS/HYPOTHESIS: We examined all-cause mortality trends in people with diabetes and compared them with trends among people without diabetes. METHODS: MEDLINE, EMBASE and CINAHL databases were searched for observational studies published from 1980 to 2019 reporting all-cause mortality rates across ≥2 time periods in people with diabetes. Mortality trends were examined by ethnicity, age and sex within comparable calendar periods. RESULTS: Of 30,295 abstracts screened, 35 studies were included, providing data on 69 separate ethnic-specific or sex-specific populations with diabetes since 1970. Overall, 43% (3/7), 53% (10/19) and 74% (32/43) of the populations studied had decreasing trends in all-cause mortality rates in people with diabetes in 1970-1989, 1990-1999 and 2000-2016, respectively. In 1990-1999 and 2000-2016, mortality rates declined in 75% (9/12) and 78% (28/36) of predominantly Europid populations, and in 14% (1/7) and 57% (4/7) of non-Europid populations, respectively. In 2000-2016, mortality rates declined in 33% (4/12), 65% (11/17), 88% (7/8) and 76% (16/21) of populations aged <40, 40-54, 55-69 and ≥70 years, respectively. Among the 33 populations with separate mortality data for those with and without diabetes, 60% (6/10) of the populations with diabetes in 1990-1999 and 58% (11/19) in 2000-2016 had an annual reduction in mortality rates that was similar to or greater than in those without diabetes. CONCLUSIONS/INTERPRETATION: All-cause mortality has declined in the majority of predominantly Europid populations with diabetes since 2000, and the magnitude of annual mortality reduction matched or exceeded that observed in people without diabetes in nearly 60% of populations. Patterns of diabetes mortality remain uncertain in younger age groups and non-Europid populations. REGISTRATION: PROSPERO registration ID CRD42019095974. Graphical abstract.

DECENT: differential expression with capture efficiency adjustmeNT for single-cell RNA-seq data.

MOTIVATION: Dropout is a common phenomenon in single-cell RNA-seq (scRNA-seq) data, and when left unaddressed it affects the validity of the statistical analyses. Despite this, few current methods for differential expression (DE) analysis of scRNA-seq data explicitly model the process that gives rise to the dropout events. We develop DECENT, a method for DE analysis of scRNA-seq data that explicitly and accurately models the molecule capture process in scRNA-seq experiments. RESULTS: We show that DECENT demonstrates improved DE performance over existing DE methods that do not explicitly model dropout. This improvement is consistently observed across several public scRNA-seq datasets generated using different technological platforms. The gain in improvement is especially large when the capture process is overdispersed. DECENT maintains type I error well while achieving better sensitivity. Its performance without spike-ins is almost as good as when spike-ins are used to calibrate the capture model. AVAILABILITY AND IMPLEMENTATION: The method is implemented as a publicly available R package available from https://github.com/cz-ye/DECENT. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Exercise as a diagnostic and therapeutic tool for preventing cardiovascular morbidity in breast cancer patients- the BReast cancer EXercise InTervention (BREXIT) trial protocol.

BACKGROUND: Anthracycline chemotherapy (AC) is an efficacious (neo) adjuvant treatment for early-stage breast cancer (BCa), but is associated with an increased risk of cardiac dysfunction and functional disability. Observations suggest that regular exercise may be a useful therapy for the prevention of cardiovascular morbidity but it is yet to be interrogated in a large randomised trial. The primary aims of this study are to: 1) determine if 12-months of ET commenced at the onset of AC can reduce the proportion of BCa patients with functional disability (peak VO2, < 18 ml/kg/min), and 2) compare current standard-of-care for detecting cardiac dysfunction (resting left-ventricular ejection fraction assessed from 3-dimensional echocardiography) to measures of cardiac reserve (peak exercise cardiac output assessed from exercise cardiac magnetic resonance imaging) for predicting the development of functional disability 12-months following AC. Secondary aims are to assess the effects of ET on VO2peak, left ventricular morphology, vascular stiffness, cardiac biomarkers, body composition, bone mineral density, muscle strength, physical function, habitual physical activity, cognitive function, and multidimensional quality of life. METHODS: One hundred women with early-stage BCa (40-75 years) scheduled for AC will be randomized to 12-months of structured exercise training (n = 50) or a usual care control group (n = 50). Participants will be assessed at baseline, 4-weeks following completion of AC (4-months) and at 12-months for all measures. DISCUSSION: Women diagnosed with early-stage BCa have increased cardiac mortality. More sensitive strategies for diagnosing and preventing AC-induced cardiovascular impairment are critical for reducing cardiovascular morbidity and improving long-term health outcomes in BCa survivors. TRIAL REGISTRATION: Australia & New Zealand Clinical Trials Registry (ANZCTR), ID: 12617001408370 . Registered on 5th of October 2017.

CORP: Practical tools for improving experimental design and reporting of laboratory studies of cardiovascular physiology and metabolism.

The exercise consisted of: 1) a short survey to acquire baseline data on current practices regarding the conduct of animal studies, 2) a series of presentations for promoting awareness and providing advice and practical tools for improving experimental design, and 3) a follow-up survey 12 mo later to assess whether practices had changed. The surveys were compulsory for responsible investigators (n = 16; paired data presented). Other investigators named on animal ethics applications were encouraged to participate (2017, total of 36 investigators; 2018, 37 investigators). The major findings to come from the exercise included 1) a willingness of investigators to make changes when provided with knowledge/tools and solutions that were relatively simple to implement (e.g., proportion of responsible investigators showing improved practices using a structured method for randomization was 0.44, 95% CI (0.19; 0.70), P = 0.003, and deidentifying drugs/interventions was 0.40, 95% CI (0.12; 0.68), P = 0.010); 2) resistance to change if this involved more personnel and time (e.g., as required for allocation concealment); and 3) evidence that changes to long-term practices ("habits") require time and follow-up. Improved practices could be verified based on changes in reporting within publications or documented evidence provided during laboratory visits. In summary, this exercise resulted in changed attitudes, practices, and reporting, but continued follow-up, monitoring, and incentives are required. Efforts to improve experimental rigor will reduce bias and will lead to findings with the greatest translational potential.NEW & NOTEWORTHY The goal of this exercise was to encourage preclinical researchers to improve the quality of their cardiac and metabolic animal studies by 1) increasing awareness of concerns, which can arise from suboptimal experimental designs; 2) providing knowledge, tools, and templates to overcome bias; and 3) conducting two short surveys over 12 mo to monitor change. Improved practices were identified for the uptake of structured methods for randomization, and de-identifying interventions/drugs.Listen to this article's corresponding podcast at https://ajpheart.podbean.com/e/experimental-design-survey-training-practical-tools/.

miREM: an expectation-maximization approach for prioritizing miRNAs associated with gene-set.

BACKGROUND: The knowledge of miRNAs regulating the expression of sets of mRNAs has led to novel insights into numerous and diverse cellular mechanisms. While a single miRNA may regulate many genes, one gene can be regulated by multiple miRNAs, presenting a complex relationship to model for accurate predictions. RESULTS: Here, we introduce miREM, a program that couples an expectation-maximization (EM) algorithm to the common approach of hypergeometric probability (HP), which improves the prediction and prioritization of miRNAs from gene-sets of interest. miREM has been made available through a web-server ( https://bioinfo-csi.nus.edu.sg/mirem2/ ) that can be accessed through an intuitive graphical user interface. The program incorporates a large compendium of human/mouse miRNA-target prediction databases to enhance prediction. Users may upload their genes of interest in various formats as an input and select whether to consider non-conserved miRNAs, amongst filtering options. Results are reported in a rich graphical interface that allows users to: (i) prioritize predicted miRNAs through a scatterplot of HP p-values and EM scores; (ii) visualize the predicted miRNAs and corresponding genes through a heatmap; and (iii) identify and filter homologous or duplicated predictions by clustering them according to their seed sequences. CONCLUSION: We tested miREM using RNAseq datasets from two single "spiked" knock-in miRNA experiments and two double knock-out miRNA experiments. miREM predicted these manipulated miRNAs as having high EM scores from the gene set signatures (i.e. top predictions for single knock-in and double knock-out miRNA experiments). Finally, we have demonstrated that miREM predictions are either similar or better than results provided by existing programs.