Simple reparameterization to improve convergence in linear mixed models

Slow convergence and mixing are one of the main problems of Markov chain Monte Carlo (McMC) algorithms applied to mixed models in animal breeding. Poor convergence is to a large extent caused by high posterior correlation between variance components and solutions for the levels of associated effects. A simple reparameterization of the conventional model for variance component estimation is presented which improves McMC sampling and provides the same posterior distributions as the conventional model. Reparameterization is based on the rescaling of hierarchical (random) effects in a model, which alleviates posterior correlation. The developed model is compared against the conventional model using several simulated data sets. Results show that presented reparameterization has better behaviour of associated sampling methods and is several times more efficient for the low values of heritability

Microalgal biorefinery for bulk and high-value products : Product extraction within cell disintegration

Microalgae are a promising source for proteins, lipids, and carbohydrates for the cosmetic, nutraceutical, chemical, food/feed, and biofuel industry. In comparison with soy and palm oil, microalgae can be produced in a more sustainable way. To make microalgae production economically feasible, all biomass ingredients need to be efficiently utilized, similar to petroleum refineries in which oil is fractionated in fuels and a variety of products with higher value. However severe conditions can affect the properties of some components in the biomass. To overcome this, focus needs to be put on biorefinery techniques which are mild and effective. Microalgal biorefinery is a linear process consisting of harvesting, cell disintegration, sequential extraction, and further fractionation. Among these steps, the cell disintegration often represents a bottleneck for the extraction of hydrophilic or hydrophobic components, due to the presence of a tough cell wall in many strains. State of the art knowledge on both novel and classical techniques for product extraction within cell disintegration is presented. Comparison is made on the basis of two main criteria: yield of disintegration and energy consumption. The current work gives also a comprehensive outlook on business cases for microalgae biorefinery

Microalgal Biorefinery for Bulk and High-Value Products: Product Extraction Within Cell Disintegration

Microalgae are a promising source for proteins, lipids, and carbohydrates for the cosmetic, nutraceutical, chemical, food/feed, and biofuel industry. In comparison with soy and palm oil, microalgae can be produced in a more sustainable way. To make microalgae production economically feasible, all biomass ingredients need to be efficiently utilized, similar to petroleum refineries in which oil is fractionated in fuels and a variety of products with higher value. However severe conditions can affect the properties of some components in the biomass. To overcome this, focus needs to be put on biorefinery techniques which are mild and effective. Microalgal biorefinery is a linear process consisting of harvesting, cell disintegration, sequential extraction, and further fractionation. Among these steps, the cell disintegration often represents a bottleneck for the extraction of hydrophilic or hydrophobic components, due to the presence of a tough cell wall in many strains. State of the art knowledge on both novel and classical techniques for product extraction within cell disintegration is presented. Comparison is made on the basis of two main criteria: yield of disintegration and energy consumption. The current work gives also a comprehensive outlook on business cases for microalgae biorefinery

C9orf72, age at onset, and ancestry help discriminate behavioral from language variants in FTLD cohorts

Objective: We sought to characterize C9orf72 expansions in relation to genetic ancestry and age at onset (AAO) and to use these measures to discriminate the behavioral from the language variant syndrome in a large pan-European cohort of frontotemporal lobar degeneration (FTLD) cases. / Methods: We evaluated expansions frequency in the entire cohort (n = 1,396; behavioral variant frontotemporal dementia [bvFTD] [n = 800], primary progressive aphasia [PPA] [n = 495], and FTLD–motor neuron disease [MND] [n = 101]). We then focused on the bvFTD and PPA cases and tested for association between expansion status, syndromes, genetic ancestry, and AAO applying statistical tests comprising Fisher exact tests, analysis of variance with Tukey post hoc tests, and logistic and nonlinear mixed-effects model regressions. / Results: We found C9orf72 pathogenic expansions in 4% of all cases (56/1,396). Expansion carriers differently distributed across syndromes: 12/101 FTLD-MND (11.9%), 40/800 bvFTD (5%), and 4/495 PPA (0.8%). While addressing population substructure through principal components analysis (PCA), we defined 2 patients groups with Central/Northern (n = 873) and Southern European (n = 523) ancestry. The proportion of expansion carriers was significantly higher in bvFTD compared to PPA (5% vs 0.8% [p = 2.17 × 10−5; odds ratio (OR) 6.4; confidence interval (CI) 2.31–24.99]), as well as in individuals with Central/Northern European compared to Southern European ancestry (4.4% vs 1.8% [p = 1.1 × 10−2; OR 2.5; CI 1.17–5.99]). Pathogenic expansions and Central/Northern European ancestry independently and inversely correlated with AAO. Our prediction model (based on expansions status, genetic ancestry, and AAO) predicted a diagnosis of bvFTD with 64% accuracy. / Conclusions: Our results indicate correlation between pathogenic C9orf72 expansions, AAO, PCA-based Central/Northern European ancestry, and a diagnosis of bvFTD, implying complex genetic risk architectures differently underpinning the behavioral and language variant syndromes

C9orf72, age at onset, and ancestry help discriminate behavioral from language variants in FTLD cohorts

Objective: We sought to characterize C9orf72 expansions in relation to genetic ancestry and age at onset (AAO) and to use these measures to discriminate the behavioral from the language variant syndrome in a large pan-European cohort of frontotemporal lobar degeneration (FTLD) cases. Methods: We evaluated expansions frequency in the entire cohort (n = 1,396; behavioral variant frontotemporal dementia [bvFTD] [n = 800], primary progressive aphasia [PPA] [n = 495], and FTLD-motor neuron disease [MND] [n = 101]). We then focused on the bvFTD and PPA cases and tested for association between expansion status, syndromes, genetic ancestry, and AAO applying statistical tests comprising Fisher exact tests, analysis of variance with Tukey post hoc tests, and logistic and nonlinear mixed-effects model regressions. Results: We found C9orf72 pathogenic expansions in 4% of all cases (56/1,396). Expansion carriers differently distributed across syndromes: 12/101 FTLD-MND (11.9%), 40/800 bvFTD (5%), and 4/495 PPA (0.8%). While addressing population substructure through principal components analysis (PCA), we defined 2 patients groups with Central/Northern (n = 873) and Southern European (n = 523) ancestry. The proportion of expansion carriers was significantly higher in bvFTD compared to PPA (5% vs 0.8% [p = 2.17 × 10-5; odds ratio (OR) 6.4; confidence interval (CI) 2.31-24.99]), as well as in individuals with Central/Northern European compared to Southern European ancestry (4.4% vs 1.8% [p = 1.1 × 10-2; OR 2.5; CI 1.17-5.99]). Pathogenic expansions and Central/Northern European ancestry independently and inversely correlated with AAO. Our prediction model (based on expansions status, genetic ancestry, and AAO) predicted a diagnosis of bvFTD with 64% accuracy. Conclusions: Our results indicate correlation between pathogenic C9orf72 expansions, AAO, PCA-based Central/Northern European ancestry, and a diagnosis of bvFTD, implying complex genetic risk architectures differently underpinning the behavioral and language variant syndromes