Causal relationships between milk quality and coagulation properties in Italian Holstein-Friesian dairy cattle

Background: Recently, selection for milk technological traits was initiated in the Italian dairy cattle industry based on direct measures of milk coagulation properties (MCP) such as rennet coagulation time (RCT) and curd firmness 30 min after rennet addition (a30) and on some traditional milk quality traits that are used as predictors, such as somatic cell score (SCS) and casein percentage (CAS). The aim of this study was to shed light on the causal relationships between traditional milk quality traits and MCP. Different structural equation models that included causal effects of SCS and CAS on RCT and a30 and of RCT on a30 were implemented in a Bayesian framework. Results: Our results indicate a non-zero magnitude of the causal relationships between the traits studied. Causal effects of SCS and CAS on RCT and a30 were observed, which suggests that the relationship between milk coagulation ability and traditional milk quality traits depends more on phenotypic causal pathways than directly on common genetic influence. While RCT does not seem to be largely controlled by SCS and CAS, some of the variation in a30 depends on the phenotypes of these traits. However, a30 depends heavily on coagulation time. Our results also indicate that, when direct effects of SCS, CAS and RCT are considered simultaneously, most of the overall genetic variability of a30 is mediated by other traits. Conclusions: This study suggests that selection for RCT and a30 should not be performed on correlated traits such as SCS or CAS but on direct measures because the ability of milk to coagulate is improved through the causal effect that the former play on the latter, rather than from a common source of genetic variation. Breaking the causal link (e.g. standardizing SCS or CAS before the milk is processed into cheese) would reduce the impact of the improvement due to selective breeding. Since a30 depends heavily on RCT, the relative emphasis that is put on this trait should be reconsidered and weighted for the fact that the pure measure of a30 almost double-counts RCT

Genomic prediction with whole-genome sequence data in intensely selected pig lines

Background Early simulations indicated that whole-genome sequence data (WGS) could improve the accuracy of genomic predictions within and across breeds. However, empirical results have been ambiguous so far. Large datasets that capture most of the genomic diversity in a population must be assembled so that allele substitution effects are estimated with high accuracy. The objectives of this study were to use a large pig dataset from seven intensely selected lines to assess the benefits of using WGS for genomic prediction compared to using commercial marker arrays and to identify scenarios in which WGS provides the largest advantage. Methods We sequenced 6931 individuals from seven commercial pig lines with different numerical sizes. Genotypes of 32.8 million variants were imputed for 396,100 individuals (17,224 to 104,661 per line). We used BayesR to perform genomic prediction for eight complex traits. Genomic predictions were performed using either data from a standard marker array or variants preselected from WGS based on association tests. Results The accuracies of genomic predictions based on preselected WGS variants were not robust across traits and lines and the improvements in prediction accuracy that we achieved so far with WGS compared to standard marker arrays were generally small. The most favourable results for WGS were obtained when the largest training sets were available and standard marker arrays were augmented with preselected variants with statistically significant associations to the trait. With this method and training sets of around 80k individuals, the accuracy of within-line genomic predictions was on average improved by 0.025. With multi-line training sets, improvements of 0.04 compared to marker arrays could be expected. Conclusions Our results showed that WGS has limited potential to improve the accuracy of genomic predictions compared to marker arrays in intensely selected pig lines. Thus, although we expect that larger improvements in accuracy from the use of WGS are possible with a combination of larger training sets and optimised pipelines for generating and analysing such datasets, the use of WGS in the current implementations of genomic prediction should be carefully evaluated against the cost of large-scale WGS data on a case-by-case basis

From regenerated wood pulp fibers to cationic cellulose: preparation, characterization and dyeing properties

The global demand for sustainable textile fibers is growing and has led to an increasing research interest from both academia and industry to find effective solutions. In this research, regenerated wood pulp fibers were functionalized with glycidyltrimethylammonium chloride (GTAC) to produce modified regenerated cellulose with cationic pending groups for improved dye uptake. The resultant cationic cellulose with a degree of substitution (DS) between 0.13 and 0.33 exhibited distinct morphologies and contact angles with water ranging from 65.7◦ to 82.5◦ for the fibers with DS values of 0.13 and 0.33, respectively. Furthermore, the thermal stability of the modified regenerated cellulose fibers, albeit lower than the pristine ones, reached temperatures up to 220 ◦C. Additionally, the modified fibers showed higher dye exhaustion and dye fixation values than the non-modified ones, attaining maxima values of 89.3% ± 0.9% and 80.6% ± 1.3%, respectively, for the cationic fibers with a DS of 0.13. These values of dye exhaustion and dye fixation are ca. 34% and 77% higher than those obtained for the non-modified fibers. Overall, regenerated wood pulp cellulose fibers can be used, after cationization, as textiles fiber with enhanced dye uptake performance that might offer new options for dyeing treatments.publishe

Alginate-lysozyme nanofibers hydrogels with improved rheological behavior, printability and biological properties for 3D bioprinting applications

In this study, alginate nanocomposite hydrogel bioinks reinforced with lysozyme nanofibers (LNFs) were developed. Alginate-LNF (A-LNF) suspensions with different LNF contents (1, 5 and 10 wt.%) were prepared and pre-crosslinked with 0.5% (w/v) CaCl2 to formulate A-LNF inks. These inks exhibit proper shear-thinning behavior and good recovery properties (~90%), with the pre-crosslinking step playing a crucial role. A-LNF fully crosslinked hydrogels (with 2% (w/v) CaCl2) that mimic 3D printing scaffolds were prepared, and it was observed that the addition of LNFs improved several properties of the hydrogels, such as the morphology, swelling and degradation profiles, and mechanical properties. All formulations are also noncytotoxic towards HaCaT cells. The printing parameters and 3D scaffold model were then optimized, with A-LNF inks showing improved printability. Selected A-LNF inks (A-LNF0 and A-LNF5) were loaded with HaCaT cells (cell density 2 × 106 cells mL-1), and the cell viability within the bioprinted scaffolds was evaluated for 1, 3 and 7 days, with scaffolds printed with the A-LNF5 bioink showing the highest values for 7 days (87.99 ± 1.28%). Hence, A-LNF bioinks exhibited improved rheological performance, printability and biological properties representing a good strategy to overcome the main limitations of alginate-based bioinks.publishe

Searching for phenotypic causal networks involving complex traits: an application to European quail

<p>Abstract</p> <p>Background</p> <p>Structural equation models (SEM) are used to model multiple traits and the casual links among them. The number of different causal structures that can be used to fit a SEM is typically very large, even when only a few traits are studied. In recent applications of SEM in quantitative genetics mixed model settings, causal structures were pre-selected based on prior beliefs alone. Alternatively, there are algorithms that search for structures that are compatible with the joint distribution of the data. However, such a search cannot be performed directly on the joint distribution of the phenotypes since causal relationships are possibly masked by genetic covariances. In this context, the application of the Inductive Causation (IC) algorithm to the joint distribution of phenotypes conditional to unobservable genetic effects has been proposed.</p> <p>Methods</p> <p>Here, we applied this approach to five traits in European quail: birth weight (BW), weight at 35 days of age (W35), age at first egg (AFE), average egg weight from 77 to 110 days of age (AEW), and number of eggs laid in the same period (NE). We have focused the discussion on the challenges and difficulties resulting from applying this method to field data. Statistical decisions regarding partial correlations were based on different Highest Posterior Density (HPD) interval contents and models based on the selected causal structures were compared using the Deviance Information Criterion (DIC). In addition, we used temporal information to perform additional edge orienting, overriding the algorithm output when necessary.</p> <p>Results</p> <p>As a result, the final causal structure consisted of two separated substructures: BW→AEW and W35→AFE→NE, where an arrow represents a direct effect. Comparison between a SEM with the selected structure and a Multiple Trait Animal Model using DIC indicated that the SEM is more plausible.</p> <p>Conclusions</p> <p>Coupling prior knowledge with the output provided by the IC algorithm allowed further learning regarding phenotypic causal structures when compared to standard mixed effects SEM applications.</p

QSAR-Driven Discovery of Novel Chemical Scaffolds Active against Schistosoma mansoni.

Schistosomiasis is a neglected tropical disease that affects millions of people worldwide. Thioredoxin glutathione reductase of Schistosoma mansoni (SmTGR) is a validated drug target that plays a crucial role in the redox homeostasis of the parasite. We report the discovery of new chemical scaffolds against S. mansoni using a combi-QSAR approach followed by virtual screening of a commercial database and confirmation of top ranking compounds by in vitro experimental evaluation with automated imaging of schistosomula and adult worms. We constructed 2D and 3D quantitative structure-activity relationship (QSAR) models using a series of oxadiazoles-2-oxides reported in the literature as SmTGR inhibitors and combined the best models in a consensus QSAR model. This model was used for a virtual screening of Hit2Lead set of ChemBridge database and allowed the identification of ten new potential SmTGR inhibitors. Further experimental testing on both shistosomula and adult worms showed that 4-nitro-3,5-bis(1-nitro-1H-pyrazol-4-yl)-1H-pyrazole (LabMol-17) and 3-nitro-4-{[(4-nitro-1,2,5-oxadiazol-3-yl)oxy]methyl}-1,2,5-oxadiazole (LabMol-19), two compounds representing new chemical scaffolds, have high activity in both systems. These compounds will be the subjects for additional testing and, if necessary, modification to serve as new schistosomicidal agents

Dichlorodioxomolybdenum(VI) complexes bearing oxygen-donor ligands as olefin epoxidation catalysts

Treatment of the solvent adduct [MoO2Cl2(THF)2] with either 2 equivalents of N,N-dimethylbenzamide (DMB) or 1 equivalent of N,N'-diethyloxamide (DEO) gave the dioxomolybdenum(vi) complexes [MoO2Cl2(DMB)2] () and [MoO2Cl2(DEO)] (). The molecular structures of and were determined by single-crystal X-ray diffraction. Both complexes present a distorted octahedral geometry and adopt the cis-oxo, trans-Cl, cis-L configuration typical of complexes of the type [MoO2X2(L)n], with either the monodentate DMB or bidentate DEO oxygen-donor ligands occupying the equatorial positions trans to the oxo groups. The complexes were applied as homogeneous catalysts for the epoxidation of olefins, namely cis-cyclooctene (Cy), 1-octene, trans-2-octene, α-pinene and (R)-(+)-limonene, using tert-butylhydroperoxide (TBHP) as oxidant. In the epoxidation of Cy at 55 °C, the desired epoxide was the only product and turnover frequencies in the range of ca. 3150-3200 mol molMo(-1) h(-1) could be reached. The catalytic production of cyclooctene oxide was investigated in detail, varying either the reaction temperature or the cosolvent. Complexes and were also applied in liquid-liquid biphasic catalytic epoxidation reactions by using an ionic liquid of the type [C4mim][X] (C4mim = 1-n-butyl-3-methylimidazolium; X = NTf2, BF4 or PF6] as a solvent to immobilise the metal catalysts. Recycling for multiple catalytic runs was achieved without loss of activity