Colostrum source and passive immunity transfer in dairy bull calves

Colostrum is essential for good neonate health; however, it is not known whether different calves absorb the nutrients from colostrum equally well. In this study, the absorption of protein, IgG, and γ-glutamyl transferase was compared in newborn dairy bull calves for 1 wk after feeding colostrum from different sources. Thirty-five Holstein-Friesian bull calves were randomly allocated into 3 groups and fed colostrum within 4 h after birth. Group A calves (n = 12) were bottle fed colostrum from their own dam for 3 d. Colostrum from these group A cows was also used as foster cow colostrum for the group B calves (n = 12), such that each group A and B calf pair received identical colostrum from each milking of the respective group A dam (10% of birth weight per day). The group C calves (n = 11) were fed 1 bottle (2 L) of pooled colostrum and transition milk (referred to as pooled colostrum), as was the standard practice on the dairy farm. The pooled colostrum was collected from the other dairy cows on the farm 0 to 4 d postpartum and stored at 4°C for less than 12 h. Blood was sampled from calves before the first feeding and at 1, 2, 3, and 7 d after birth. Levels of total solids, total protein, and IgG were higher in the dam colostrum than in the pooled colostrum. At birth, there were no differences between the calf groups for any measurements, and all calves had very low IgG levels. After receiving colostrum, the glucose, plasma γ-glutamyl transferase, serum total protein, and IgG concentrations increased significantly in all calves. There were no differences in any blood measurements at any time point between the pairs of group A and group B calves that received colostrum from the same cow except for the IgG concentration 2 d after birth. However, the group A calves had a higher total serum protein level and IgG concentration than the group C calves for all the time points after the first feeding. The group B calves had a higher IgG concentration than the group C calves on d 1, 2, and 7 after birth. Compared with groups A and B, there was no difference in the proportion of calves in group C that failed to have passive immunity transferred adequately based on the IgG threshold (<10 g/L). Thus, the calves receiving identical colostrum from the same cow had the same levels of IgG, and even the pooled colostrum provided sufficient transfer of IgG as the calves were fed within 4 h after birth.     

Evaluation of the degree of rate control via automatic differentiation

The degree of rate control (DRC) quantitatively identifies the kinetically relevant (sometimes known as rate-limiting) steps of a complex reaction network. This concept relies on derivatives which are commonly implemented numerically, for example, with finite differences (FDs). Numerical derivatives are tedious to implement, and can be problematic, and unstable or unreliable. In this study, we demonstrate the use of automatic differentiation (AD) in the evaluation of the DRC. AD libraries are increasingly available through modern machine learning frameworks. Compared with the FDs, AD provides solutions with higher accuracy with lower computational cost. We demonstrate applications in steady-state and transient kinetics. Furthermore, we illustrate a hybrid local-global sensitivity analysis method, the distributed evaluation of local sensitivity analysis, to assess the importance of kinetic parameters over an uncertain space. This method also benefits from AD to obtain high-quality results efficiently.     

Cyanogenic,carotenoids and protein composition in leaves and roots across seven diverse population found in the world cassava germplasm collection at CIAT,Colombia

The objective of this study was to characterise the nutritional potential of leaves and identify a diversity centre with low cyanide and high nutrient content among 178 Latin American cassava genotypes. This field-based collection represents the seven diversity centres, held at The International Center for Tropical Agriculture (CIAT Palmira, Colombia) by the Cassava Program. The cyanide, all-trans-β-carotene and lutein concentrations in cassava leaves ranged from 346 to 7484 ppm dry basis (db), from 174–547 μg g⁻¹ db and 15–181 μg g⁻¹ db, respectively. Cassava leaves also showed significant levels of essential amino acids leucine, lysine, phenylalanine, valine and threonine, and average total protein content of 26.24 g 100 g⁻¹ db. Among seven diversity centres, South American rainforest group showed low cyanide and high carotene content in leaves. In addition, VEN77 and PAN51 genotypes stood out for having low cyanide in leaves and roots and high carotene in leaves. This genetic diversity can be used to select high potential progenitors for breeding purposes.     

Biocatalytic Alkylation Cascades: Recent Advances and Future Opportunities for Late-Stage Functionalization

This Concept article describes the latest developments in the emerging area of late-stage biocatalytic alkylation. Central to these developments is the ability to efficiently prepare S-adenosyl methionine (SAM) cofactor analogues and couple this with enzymatic alkyl transfer. Recent developments in the enzymatic synthesis of SAM cofactor analogues are summarized first, followed by their application as alkyl transfer agents catalyzed by methyltransferases (MTases). Second, innovative methods to regenerate SAM cofactors by enzymatic cascades is reported. Finally, future opportunities towards establishing a generalized platform for late-stage alkylation are described.     

Dietary Alcohol and Fat Differentially Affect Plasma Cholesteryl Ester Transfer Activity and Triglycerides in Normo- and Hypertriglyceridemic Subjects

Moderate alcohol consumption is associated with increased plasma high-density lipoprotein (HDL)-cholesterol concentrations and reduced risk for cardiovascular disease. Plasma cholesteryl ester transfer activity (CETA) mediates the exchange of HDL-cholesteryl ester (CE) for the triacylglycerol (TAG) of very-low-density lipoproteins. We compared the effects of oral challenges of Alcohol, saturated fat (SAT), and (Alcohol + SAT) on plasma CETA, cholesterol, nonesterified fatty acids (NEFA), and TAG among normo-triglyceridemic (NTG) and mildly hypertriglyceridemic (HTG) volunteers having a range of plasma TAG concentrations. The major changes were (1) CETA increased more after ingestion of SAT and (Alcohol + SAT) in the HTG group versus the NTG group; (2) after all three challenges, elevation of plasma TAG concentration persisted longer in the HTG versus NTG group. Plasma cholesterol was not affected by the three dietary challenges, while Alcohol increased NEFA more in the HTG group than the NTG group. Plasma TAG best predicted plasma CETA, suggesting that intestinally derived lipoproteins are acceptors of HDL-CE. Unexpectedly, ingestion of (Alcohol + SAT) reduced the strength of the correlation between plasma TAG and CETA, that is the effects of (SAT and Alcohol) on plasma CETA are not synergistic nor additive but rather mutually suppressive. The alcohol-mediated inhibition of CE-transfer to chylomicrons maintains a higher plasma HDL-cholesterol concentration, which is athero-protective, although the suppressive metabolite underlying this correlation could be acetate, the terminal alcohol metabolite, other factors, including CETA inhibitors, are also likely important.     

Three‐dimensional color prediction modeling of single‐ and double‐layered woven fabrics

In this research, the three‐dimensional structural and colorimetric modeling of three‐dimensional woven fabrics was conducted for accurate color predictions. One‐hundred forty single‐ and double‐layered woven samples in a wide range of colors were produced. With the consideration of their three‐dimensional structural parameters, three‐dimensional color prediction models, K/S‐, R‐, and L*a*b*‐based models, were developed through the optimization of previous two‐dimensional models which have been reported to be the three most accurate models for single‐layered woven structures. The accuracy of the new three‐dimensional models was evaluated by calculating the color differences ΔL*, ΔC*, Δh°, and ΔE_CMC(2:1) between the measured and the predicted colors of the samples, and then the error values were compared to those of the two‐dimensional models. As a result, there has been an overall improvement in color predictions of all models with a decrease in ΔE_CMC(2:1) from 10.30 to 5.25 units on average after the three‐dimensional modeling.