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Background: Mendelian randomization analysis was applied to elucidate the causal relationship between the basal metabolic rate (BMR) and common cardiovascular diseases. Method: We choose BMR as exposure. BMR is the metabolic rate of the body when the basic physiological activities (blood circulation, breathing and constant body temperature) are maintained. The normal BMR is 1507 kcal/day for men and 1276 kcal/day for women. The dataset was drawn from the public GWAS dataset (GWAS ID: ukb‐a‐268), collected and analysed by UK biobank, containing 331,307 European males and females. SNPs independently and strongly associated with BMR were used as instrumental variables in the inverse variance weighted analysis. MR‐Egger, weighted median, MR pleiotropy residual sum, and outlier methods were also performed, and the sensitivity was evaluated using horizontal pleiotropy and heterogeneity analyses to ensure the stability of the results. Results: An increased BMR is associated with a higher risk of cardiomyopathy (odds ratio [OR] = 2.00, 95% confidence interval [CI], 1.57–2.54, p = 1.87 × 10−8), heart failure (OR = 1.39, 95% CI, 1.27–2.51, p = 8.1 × 10−13), and valvular heart disease (OR = 1.18, 95% CI, 1.10–1.27, p =.00001). However, there was no clear association between BMR and the subtypes of other cardiovascular diseases, such as coronary disease (OR =.96, 95% CI,.85–1.08, p =.48651) and atrial fibrillation (AF) (OR = 1.85, 95% CI, 1.70–2.02, p = 6.28 × 10−44). Conclusion: Our study reveals a possible causal effect of BMR on the risk of cardiomyopathy, heart failure and valvular disease, but not for coronary disease and AF. [ABSTRACT FROM AUTHOR]

It is an inevitable trend of the development of world first-class universities to promote the construction of a powerful country in higher education and to build and own a number of world first-class universities around the world. Under the actual background of the construction of "world first-class university," this paper studies the comprehensive evaluation of university competitiveness. Firstly, considering the selection condition and development tasks of "world first-class university," 13 indexes are selected to construct a comprehensive evaluation index system of university competitiveness from six aspects of talent training, scientific research, teacher construction, social service, social reputation and internationalization degree, and the method of principal component analysis (PCA) is used to determine the weights of these 13 indexes. Secondly, a new Deviation Degree-Technique for Order Preference by Similarity to Ideal Solution (DD-TOPSIS) method is proposed to comprehensively evaluate the university competitiveness. Thirdly, 15 universities in Hubei Province of China and 10 top universities in UK are selected for empirical analysis, respectively. Finally, according to the results of empirical analysis, some suggestions on the construction of "world first-class university" are provided from the aspects of teacher construction, talent training, social service and university management. [ABSTRACT FROM AUTHOR]

Background The burden of chronic conditions associated with sugary beverages is increasing but little is known about the role of different types of sugary beverages in the co-occurrence of multiple chronic conditions ('multimorbidity'). To inform future sugar-reduction guidelines, we aimed to examine the associations of sugar-sweetened beverages (SSB), artificially sweetened beverages (ASB) and natural juices (NJ) with multimorbidity. Methods This prospective cohort study included 184 093 UK Biobank participants aged 40–69 years at baseline who completed at least one occasion of 24-h dietary recall between 2009 and 2012. Daily consumptions of SSB, ASB and NJ were assessed using 24-h dietary recall. Participants were followed from the first 24-h assessment until the onset of two or more new chronic conditions, or the end of follow-up (31 March 2017), whichever occurred first. Logistic regression models, Cox proportional hazard models and quasi-Poisson mixed effects models were used to estimate the association of beverages intakes with chronic conditions and multimorbidity. Results A total of 19 057 participants had multimorbidity at baseline and 19 968 participants developed at least two chronic conditions during follow-up. We observed dose–response relationships of SSB and ASB consumptions with the prevalence and incidence of multimorbidity. For example, the adjusted hazard ratios (HRs) and 95% CIs of the incidence of developing at least two chronic conditions ranged from 1.08 (1.01–1.14) for SSB intake of 1.1–2 units/day to 1.23 (1.14–1.32) for >2 units/day compared with 0 units/day. Also, the adjusted HRs (95% CIs) of ASB consumption ranged from 1.08 (1.03–1.13) for 0.1–1 unit/day to 1.28 (1.17–1.40) for >2 units/day compared with non-consumers. Conversely, moderate consumption of NJ was associated with a smaller risk of the prevalence and incidence of multimorbidity. Moreover, higher intakes of SSB and ASB were positively associated whereas moderate intake of NJ was inversely associated with increased number of new-onset chronic conditions during follow-up. Conclusions Higher SSB and ASB intakes were positively associated whereas moderate NJ intake was inversely associated with the higher risk of multimorbidity and increased number of chronic conditions. Current and intended policy options to decrease the burden of chronic conditions and multimorbidity need a formulation of SSB and ASB reduction strategies. [ABSTRACT FROM AUTHOR]

The United Kingdom (UK) has a decarbonisation strategy that includes energy from both hydrogen and biomethane. The latter comes from the growing anaerobic digestion (AD) market, which in 2020 produced 23.3 TWh of energy in the form of biogas. According to the strategy, this must be upgraded to biomethane by removal of carbon dioxide (CO2): a goal that could also be fulfilled through CO2 biomethanisation, alleviating the need for carbon capture and storage. Results are presented from a survey of publicly available datasets coupled with modelling to identify potential scale and knowledge gaps. Literature data were used to estimate maximum biomethane concentrations by feedstock type: these ranged from 79% for food wastes to 93% for livestock manures. Data from various government sources were used to estimate the overall potential for CO2 biomethanisation with current AD infrastructure. Values for the uplift in biomethane production ranged from 57% to 61%, but the need for more consistent data collection methodologies was highlighted. On average, however, if CO2 biomethanisation was applied in all currently operating UK AD plants an energy production uplift of 12,954 GWh could be achieved based on 2020 figures. This is sufficient to justify the inclusion of CO2 biomethanisation in decarbonisation strategies, in the UK and worldwide. [ABSTRACT FROM AUTHOR]

With the development of genome-wide association studies, how to gain information from a large scale of data has become an issue of common concern, since traditional methods are not fully developed to solve problems such as identifying loci-to-loci interactions (also known as epistasis). Previous epistatic studies mainly focused on local information with a single outcome (phenotype), while in this paper, we developed a two-stage global search algorithm, Greedy Equivalence Search with Local Modification (GESLM), to implement a global search of directed acyclic graph in order to identify genome-wide epistatic interactions with multiple outcome variables (phenotypes) in a case–control design. GESLM integrates the advantages of score-based methods and constraint-based methods to learn the phenotype-related Bayesian network and is powerful and robust to find the interaction structures that display both genetic associations with phenotypes and gene interactions. We compared GESLM with some common phenotype-related loci detecting methods in simulation studies. The results showed that our method improved the accuracy and efficiency compared with others, especially in an unbalanced case–control study. Besides, its application on the UK Biobank dataset suggested that our algorithm has great performance when handling genome-wide association data with more than one phenotype. [ABSTRACT FROM AUTHOR]

To determine whether the neutralization activity of monoclonal antibodies, convalescent sera and vaccine-elicited sera was affected by the top five epidemic SARS-CoV-2 variants in the UK, including D614G+L18F+A222V, D614G+A222V, D614G+S477N, VOC-202012/01(B.1.1.7) and D614G+69-70del+N439K, a pseudovirus-neutralization assay was performed to evaluate the relative neutralization titers against the five SARS-CoV-2 variants and 12 single deconvolution mutants based on the variants. In this study, 18 monoclonal antibodies, 10 sera from convalescent COVID-19 patients, 10 inactivated-virus vaccine-elicited sera, 14 mRNA vaccine-elicited sera, nine RBD-immunized mouse sera, four RBD-immunized horse sera, and four spike-encoding DNA-immunized guinea pig sera were tested and analyzed. The N501Y, N439K, and S477N mutations caused immune escape from nine of 18 mAbs. However, the convalescent sera, inactivated virus vaccine-elicited sera, mRNA vaccine-elicited sera, spike DNA-elicited sera, and recombinant RBD protein-elicited sera could still neutralize these variants (within three-fold changes compared to the reference D614G variant). The neutralizing antibody responses to different types of vaccines were different, whereby the response to inactivated-virus vaccine was similar to the convalescent sera. [ABSTRACT FROM AUTHOR]

While it is well known that particle size reduction impacts the performance of bioprocessing such as anaerobic digestion or composting, there is a relative lack of knowledge about particle size distribution (PSD) in pre-treated organic material, i.e., the distribution of particles across different size ranges. PSD in municipal solid waste (MSW) pre-treated for bioprocessing in mechanical–biological treatment (MBT) was researched. In the first part of this study, the PSD in pre-treated waste at two full-scale MBT plants in the UK was determined. The main part of the study consisted of experimental trials to reduce particle sizes in MSW destined for bioprocessing and to explore the obtained PSD patterns. Shredders and a macerating grinder were used. For shear shredders, a jaw opening of 20 mm was found favourable for effective reduction of particle sizes, while a smaller jaw opening rather compressed the wet organic waste into balls. Setting the shredder jaw opening to 20 mm does not mean that in the output all particles will be 20 mm or below. PSD profiles revealed that different particle sizes were present in each trial. Using different types of equipment in series was effective in reducing the presence of larger particles. Maceration yielded a PSD dominated by very fine particles, which is unsuitable for composting and potentially also for anaerobic digestion. It was concluded that shredding, where equipment is well selected, is effective in delivering a material well suited for anaerobic digestion or composting. [ABSTRACT FROM AUTHOR]

Purpose: Gestational diabetes mellitus (GDM) could increase the risks of type 2 diabetes mellitus (T2DM) and cardiovascular disease. However, evidence on its association with cardiometabolic multimorbidity (CMM) was limited. This study aimed to evaluate the association between GDM and the prevalence, incidence, patterns, and progression of CMM; and the role of body mass index (BMI) in such association., Methods: This study included 203,372 women who have given birth in UK Biobank. The diagnoses of GDM and cardiometabolic diseases (including stroke, coronary heart disease [CHD], and T2DM) were reported by participants or obtained through linkage to inpatient hospital data until 31st December 2020. BMI was assessed at the baseline assessment. CMM was defined as having two or more of included cardiometabolic diseases. Logistic regression models and Cox proportional hazard models were used to assess the association between GDM and CMM, and the modifications on both additive and multiplicative scales were assessed to evaluate the effect of BMI on such association., Results: A total of 1217 women had a history of GDM, 2351 participants had CMM at the end of follow-up and 1601 was newly diagnosed during follow-up. GDM was associated with higher prevalence (odds ratio [OR]=4.64, 95 % confidence interval [95 % CI]=3.54-6.08) and incidence (hazard ratio [HR]=3.62, 95 % CI=2.62-5.00) of CMM. In particular, GDM was associated with higher odds of T2DM, coexisting T2DM and vascular disease, and T2DM followed by vascular disease. Formal testing for effect modification suggested multiplicative modification by BMI for the association between GDM and incident CMM., Conclusions: GDM was associated with CMM in women's late life, with multiplicative modification effects of BMI. Our results suggest that maternal and lifestyle interventions (e.g., weight management) are warranted for the primary and secondary prevention of CMM, particularly in women with a history of GDM., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background & Aims: Body mass index and waist circumference are simple measures of obesity. However, they do not distinguish between visceral and subcutaneous fat, or muscle, potentially leading to biased relationships between individual body composition parameters and adverse health outcomes. The purpose of this study was to develop and validate prediction models for volumetric adipose and muscle., Methods: Based on cross-sectional data of 18,457, 18,260, and 17,052 White adults from the UK Biobank, we developed sex-specific equations to estimate visceral adipose tissue (VAT), abdominal subcutaneous adipose tissue (ASAT), and total thigh fat-free muscle (FFM) volumes, respectively. Volumetric magnetic resonance imaging served as the reference. We used the least absolute shrinkage and selection operator and the extreme gradient boosting methods separately to fit three sequential models, the inputs of which included demographics and anthropometrics and, in some, bioelectrical impedance analysis parameters. We applied comprehensive metrics to assess model performance in the temporal validation set., Results: The equations that included more predictors generally performed better. Accuracy of the equations was moderate for VAT (percentage of estimates that differed <30% from the measured values, 70 to 78 in males, 64 to 69 in females) and good for ASAT (85 to 91 in males, 90 to 95 in females) and FFM (99 to 100 in both sexes). All the equations appeared precise (interquartile range of the difference, 0.89 to 1.76 L for VAT, 1.16 to 1.61 L for ASAT, 0.81 to 1.39 L for FFM). Bias of all the equations was negligible (-0.17 to 0.05 L for VAT, -0.10 to 0.12 L for ASAT, -0.07 to 0.09 L for FFM). The equations achieved superior cardiometabolic correlations compared with body mass index and waist circumference., Conclusions: The developed equations to estimate VAT, ASAT, and FFM volumes achieved moderate to good performance. They may be cost-effective tools to revisit the implications of diverse body components., Competing Interests: Conflict of interest None declared., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Magnetic resonance imaging (MRI) is the gold standard for evaluating body composition. However, the reference ranges have not been established., Methods: Three lean tissue and seven adipose tissue parameters based on MRI data from the UK Biobank were used in this study. Participants with European ancestry and data on at least one parameter were screened. Age- and sex-specific percentile curves were generated using the lambda-mu-sigma method. Three levels of reference ranges were provided, which were equivalent to the mean ± 1 standard deviation (SD), 2 SDs and 2.5 SDs., Results: The final analysis set for each parameter ranged from 4842 to 14 148 participants (53.4%-56.6% women) with a median age of 61. For lean tissue parameters, compared with those at age 45, the median total lean tissue volume and total thigh fat-free muscle volume at age 70 were 2.83 and 1.73 L, and 3.02 and 1.51 L lower in men and women, respectively. The median weight-to-muscle ratios at age 45 were 0.51 and 0.83 kg/L lower compared with those at age 70 in men and women, respectively. Adipose tissue parameters showed inconsistent differences. In men, the median muscle fat infiltration, visceral adipose tissue (VAT) volume, total abdominal adipose tissue index and abdominal fat ratio were 1.48%, 0.32 L, 0.08 L/m 2 and 0.4 higher, and the median abdominal subcutaneous adipose tissue (ASAT) volume and total adipose tissue volume were 0.47 and 0.41 L lower, respectively, at age 70 than at age 45. The median total trunk fat volume was approximately 9.53 L at all ages. In women, the median muscle fat infiltration and VAT volume were 1.68% and 0.76 L higher, respectively, at age 70 than at age 45. The median ASAT volume, total adipose tissue volume, total trunk fat volume, total abdominal adipose tissue index and abdominal fat ratio were 0.35 L, 0.78 L, 1.12 L, 0.49 L/m 2 and 0.06 higher, respectively, at age 60 than at age 45. The medians of the former three parameters were 0.33 L, 0.14 L and 0.20 L lower, at age 70 than at age 60. The medians of the latter two parameters were approximately 3.64 L/m 2 and 0.55 at ages between 60 and 70., Conclusions: We have established reference ranges for MRI-measured body composition parameters in a large community-dwelling population. These findings provide a more accurate assessment of abnormal adipose and muscle conditions., (© 2023 The Authors. Journal of Cachexia, Sarcopenia and Muscle published by John Wiley & Sons Ltd on behalf of Society on Sarcopenia, Cachexia and Wasting Disorders.)