Catch crop strategy and nitrate leaching following grazed grass-clover

Cultivation of grassland presents a high risk of nitrate leaching. This study aimed to determine if leaching could be reduced by growing spring barley (Hordeum vulgare L.) as a green crop for silage with undersown Italian ryegrass (Lolium multiflorum Lam.) compared with barley grown to maturity with or without an undersown conventional catch crop of perennial ryegrass (Lolium perenne L.). All treatments received 0,60 or 120 kg of ammonium-N ha-1 in cattle slurry. In spring 2003, two grass-clover fields (3 and 5 years old, respectively, with different management histories) were ploughed. The effects of the treatments on yield and nitrate leaching were determined in the first year, while the residual effects of the treatments were determined in the second year in a crop of spring barley⁄perennial ryegrass. Nitrate leaching was estimated in selected treatments using soil water samples from ceramic cups. The experiment showed that compared with treatments without catch crop, green barley⁄Italian ryegrass reduced leaching by 163–320 kg Nha-1, corresponding to 95–99%, and the perennial ryegrass reduced leaching to between 34 and 86 kg Nha-1, corresponding to a reduction of 80 and 66%. Also, in the second growing season, leaching following catchcrops was reduced compared with the bare soil treatment. It was concluded that the green barley⁄Italian ryegrass offers advantages not only for the environment but also for farmers, for whom it provides a fodder high in roughage and avoids the difficulties with clover fatigue increasingly experienced by Danish farmers

Greater pQCT calf muscle density is associated with lower fracture risk, independent of FRAX, falls and BMD: a meta-analysis in the osteoporotic fractures in men (MrOS) study

We investigated the predictive performance of peripheral quantitative computed tomography (pQCT) measures of both calf muscle density (an established surrogate for muscle adiposity, with higher values indicating lower muscle adiposity and higher muscle quality) and size (cross-sectional area [CSA]) for incident fracture. pQCT (Stratec XCT2000/3000) measurements at the tibia were undertaken in Osteoporotic Fractures in Men (MrOS) United States (US), Hong Kong (HK), and Swedish (SW) cohorts. Analyses were by cohort and synthesized by meta-analysis. The predictive value for incident fracture outcomes, illustrated here for hip fracture (HF), using an extension of Poisson regression adjusted for age and follow-up time, was expressed as hazard ratio (HR) per standard deviation (SD) increase in exposure (HR/SD). Further analyses adjusted for femoral neck (fn) bone mineral density (BMD) T-score, Fracture Risk Assessment Tool (FRAX) 10-year fracture probability (major osteoporotic fracture) and prior falls. We studied 991 (US), 1662 (HK), and 1521 (SW) men, mean ± SD age 77.0 ± 5.1, 73.9 ± 4.9, 80 ± 3.4 years, followed for a mean ± SD 7.8 ± 2.2, 8.1 ± 2.3, 5.3 ± 2.0 years, with 31, 47, and 78 incident HFs, respectively. Both greater muscle CSA and greater muscle density were associated with a lower risk of incident HF [HR/SD: 0.84; 95% confidence interval [CI], 0.72–1.0 and 0.78; 95% CI, 0.66–0.91, respectively]. The pattern of associations was not materially changed by adjustment for prior falls or FRAX probability. In contrast, after inclusion of fn BMD T-score, the association for muscle CSA was no longer apparent (1.04; 95% CI, 0.88–1.24), whereas that for muscle density was not materially changed (0.69; 95% CI, 0.59–0.82). Findings were similar for osteoporotic fractures. pQCT measures of greater calf muscle density and CSA were both associated with lower incidence of fractures in older men, but only muscle density remained an independent risk factor for fracture after accounting for fn BMD. These findings demonstrate a complex interplay between measures of bone, muscle size, and quality, in determining fracture risk. © 2022 The Authors. JBMR Plus published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research

New insights into the genetic etiology of Alzheimer's disease and related dementias

Characterization of the genetic landscape of Alzheimer's disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/'proxy' AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele

Utilising computational fluid dynamics (CFD) for the modelling of granular material in large-scale engineering processes

In this paper, the framework is described for the modelling of granular material by employing Computational Fluid Dynamics (CFD). This is achieved through the use and implementation in the continuum theory of constitutive relations, which are derived in a granular dynamics framework and parametrise particle interactions that occur at the micro-scale level. The simulation of a process often met in bulk solids handling industrial plants involving granular matter, (i.e. filling of a flat-bottomed bin with a binary material mixture through pneumatic conveying-emptying of the bin in core flow mode-pneumatic conveying of the material coming out of a the bin) is presented. The results of the presented simulation demonstrate the capability of the numerical model to represent successfully key granular processes (i.e. segregation/degradation), the prediction of which is of great importance in the process engineering industry