The effect of colostrum storage conditions on dairy heifer calf serum immunoglobulin G concentration and preweaning health and growth rate

The objective of the present study was to compare serum IgG concentration, weight gain, and health characteristics in Irish spring-born dairy calves fed colostrum stored using a range of conditions. Immediately after birth, 75 dairy heifer calves were assigned to 1 of 5 experimental colostrum treatments: (1) fresh pasteurized colostrum, fed immediately after pasteurization; (2) fresh colostrum, fed immediately after collection but not pasteurized; (3) colostrum stored unpasteurized at 4°C in a temperature-controlled unit for 2 d before being fed to calves; (4) colostrum stored unpasteurized at 13°C in a temperature-controlled unit for 2 d before being fed to calves; and (5) colostrum stored unpasteurized at 22°C in a temperature-controlled unit for 2 d before being fed to calves. All colostrum had IgG concentrations >50 g/L and was fed to calves promptly after birth. Blood samples were obtained from calves via the jugular vein at 0 h (before colostrum feeding) and at 24 h of age to determine the rate of passive transfer of IgG; individual calf live-weights were recorded to monitor weight gain (kg/d) from birth to weaning. Colostrum stored in warmer conditions (i.e., 22°C) had >42 times more bacteria present and a pH that was 0.85 units lower and resulted in a serum IgG concentration that was almost 2 times lower compared with colostrum that was pasteurized, untreated, or stored at 4°C for 2 d. Colostrum stored at 4°C for 2 d had more bacteria present than pasteurized and fresh colostrum but did not result in reduced calf serum IgG concentrations. Average daily weight gain from birth to weaning did not differ among treatments. Even if colostrum has sufficient IgG (>50 g/L) but cannot be fed to calves when freshly collected, storage at ≤4°C for 2 d is advisable to ensure adequate passive transfer when it is consumed by the calf.     

Void reactivity coefficient benchmark results for a 10 × 10 BWR assembly in the full 0–100% void fraction range

A boiling water reactor SVEA-96+ fresh fuel lattice has been used as the basis for a benchmark study of the void reactivity coefficient at assembly level in the full voidage range. Results have been obtained using the deterministic codes CASMO-4, HELIOS, PHOENIX, BOXER and the probabilistic code MCNP4C, combined for almost all cases with different cross section libraries. A statistical analysis of the results obtained showed that the void reactivity coefficient tends to become less negative beyond 80% void and that the discrepancies between codes tend to increase from less than 15% at voidages lower than 40% to more than 25% at voidages higher than 70%. The void reactivity coefficient results and the corresponding differences between codes were isotopically decomposed to interpret discrepancies. The isotopic decomposition shows that the minimum observed in the void reactivity coefficient between 80% and 90% void is largely due to the decrease in the relative importance of the ¹⁵⁷Gd(n, γ) rate with increasing voidage, and that the fundamental discrepancies between codes or libraries are mainly governed by the different predictions of the ²³⁸U(n, γ) variation with voidage.     

Rerandomization tests for analyzing correlated data from dental studies

Dental research studies often produce relatively small data sets in which observations are serially or spatially correlated. Rerandomization tests are presented as alternatives to analysis of variance and multivariate analysis for assessing group differences using such data. Rerandomization tests are particularly useful when the investigator is unwilling to make strong assumptions about the nature of the serial correlation or the distribution of the data. Two examples are discussed that demonstrate these techniques.     

Hematopoietic Progenitors and the Bone Marrow Niche Shape the Inflammatory Response and Contribute to Chronic Disease

It is now well understood that the bone marrow (BM) compartment can sense systemic inflammatory signals and adapt through increased proliferation and lineage skewing. These coordinated and dynamic alterations in responding hematopoietic stem and progenitor cells (HSPCs), as well as in cells of the bone marrow niche, are increasingly viewed as key contributors to the inflammatory response. Growth factors, cytokines, metabolites, microbial products, and other signals can cause dysregulation across the entire hematopoietic hierarchy, leading to lineage-skewing and even long-term functional adaptations in bone marrow progenitor cells. These alterations may play a central role in the chronicity of disease as well as the links between many common chronic disorders. The possible existence of a form of “memory” in bone marrow progenitor cells is thought to contribute to innate immune responses via the generation of trained immunity (also called innate immune memory). These findings highlight how hematopoietic progenitors dynamically adapt to meet the demand for innate immune cells and how this adaptive response may be beneficial or detrimental depending on the context. In this review, we will discuss the role of bone marrow progenitor cells and their microenvironment in shaping the scope and scale of the immune response in health and disease.     

Autonomous Vehicles and Embedded Artificial Intelligence: The Challenges of Framing Machine Driving Decisions

With the advent of autonomous vehicles society will need to confront a new set of risks which, for the first time, includes the ability of socially embedded forms of artificial intelligence to make complex risk mitigation decisions: decisions that will ultimately engender tangible life and death consequences. Since AI decisionality is inherently different to human decision-making processes, questions are therefore raised regarding how AI weighs decisions, how we are to mediate these decisions, and what such decisions mean in relation to others. Therefore, society, policy, and end-users, need to fully understand such differences. While AI decisions can be contextualised to specific meanings, significant challenges remain in terms of the technology of AI decisionality, the conceptualisation of AI decisions, and the extent to which various actors understand them. This is particularly acute in terms of analysing the benefits and risks of AI decisions. Due to the potential safety benefits, autonomous vehicles are often presented as significant risk mitigation technologies. There is also a need to understand the potential new risks which autonomous vehicle driving decisions may present. Such new risks are framed as decisional limitations in that artificial driving intelligence will lack certain decisional capacities. This is most evident in the inability to annotate and categorise the driving environment in terms of human values and moral understanding. In both cases there is a need to scrutinise how autonomous vehicle decisional capacity is conceptually framed and how this, in turn, impacts a wider grasp of the technology in terms of risks and benefits. This paper interrogates the significant shortcomings in the current framing of the debate, both in terms of safety discussions and in consideration of AI as a moral actor, and offers a number of ways forward.     

Aleatory Construction Based on Jamming: Stability Through Self-Confinement

The physical process of jamming could take architectural sustainability/recyclability to a whole new level. It involves achieving structural rigidity through the crowding of particles within a confined space, rather than by permanent bonding. Project Z-Form, a collaboration between a team of physicists from the JaegerLab at the University of Chicago – including PhD students Kieran Murphy and Leah Roth and professor Heinrich Jaeger – and artist Dan Peterman , sets out to develop a pourable material that not only self-supports but can also bear loads. Here they explain the project and the concepts behind it.     

Structural features of arabinoxylans from Sonalika variety of wheat: comparison between whole wheat flour and wheat bran

Arabinoxylans (AX) were extracted from Sonalika variety of wheat (whole wheat flour and wheat bran) with barium hydroxide and sodium hydroxide and purified by a combination of alcohol precipitation and glucoamylase digestion. Structural features of purified AX were elucidated by methylation analysis, ¹³C NMR, FT‐IR, periodate oxidation and optical rotation measurements. The AX showed a backbone of xylose residues with β(1–4) linkages and were branched mainly through O‐3 of xylose residues. Completely branched xylosyl residues were also present. Copyright © 2003 Society of Chemical Industry     

Effect of temperature on raw whole milk density and its potential impact on milk payment in the dairy industry

The objective of this study was to determine the effect of temperature on whole milk density measured at four different temperatures: 5, 10, 15, and 20 °C. A total of ninety-three individual milk samples were collected from morning milking of thirty-two Holstein Friesian dairy cows, of national average genetic merit, once every two weeks over a period of 4 weeks and were assessed by Fourier transform infrared spectroscopy for milk composition analysis. Density of the milk was evaluated using two different analytical methods: a portable density meter DMA35 and a standard desktop model DMA4500M (Anton Paar GmbH, UK). Milk density was analysed with a linear mixed model with the fixed effects of sampling period, temperature and analysis method; triple interaction of sampling period x analysis method x temperature; and the random effect of cow to account for repeated measures. The effect of temperature on milk density (ρ) was also evaluated including temperature (t) as covariate with linear and quadratic effects within each analytic method. The regression equation describing the curvature and density–temperature relationship for the DMA35 instrument was ρ = 1.0338−0.00017T−0.0000122T² (R² = 0.64), while it was ρ = 1.0334 + 0.000057T−0.00001T² (R² = 0.61) for DMA4500 instrument. The mean density determined with DMA4500 at 5 °C was 1.0334 g cm⁻³, with corresponding figures of 1.0330, 1.0320 and 1.0305 g cm⁻³ at 10, 15 and 20 °C, respectively. The milk density values obtained in this study at specific temperatures will help to address any bias in weight–volume calculations and thus may also improve the financial and operational control for the dairy processors in Ireland and internationally.     

Process Lethality Prediction for Escherichia coli O157:H7 in Raw Franks During Cooking and Fully Cooked Franks During Post-cook Pasteurization

ABSTRACT: Thermal inactivation D (decimal reduction time at a certain heating temperature) values of Escherichia coli O157:H7 at 55 °C to 70 °C were 21.36 to 0.031 min in raw franks and 24.91 to 0.038 min in fully cooked franks. Although statistically significant differences were found on the D values of E. coli O157:H7 between raw and fully cooked franks, the z value of E. coli O157:H7 in raw franks (5.07 °C) and fully cooked franks (5.08 °C) was not significantly different. The obtained D and z values were used to validate the process lethality of the pathogen in the raw franks that were processed according to a multistage cooking/cooling schedule or in the fully cooked franks that were pasteurized in-packages via steam. In this study, the calculated process lethality for both the cooking (process lethality = 254 min) and post-cook pasteurization (process lethality = 39 min) processes was far greater than the processing time that was needed for achieving a 7D reduction of E. coli O157:H7 during cooking and post-cook pasteurization of the franks.     

Evaluation of surimi, fat and water content in a low/no added pork sausage formulation using response surface methodology

Response surface methodology (RSM) was employed for simultaneous analysis of the effects of added surimi (0-40%), fat (5-30%) and water (10-35%), on the physical, textural and sensory characteristics of fresh breakfast pork sausages. Experimental design allowed for evaluation of potential interactive effects between these ingredients. Sausages were evaluated for texture, colour, water holding capacity (WHC) and sensory attributes. Three optimum recipes, R1 (25.3% surimi, 22.2% fat, 12.7% water, 25.3% pork), R2 (12.2% surimi, 5.5% fat, 38.7% water, 33.2% pork) and R3 (25.3% surimi, 6.3% fat, 28.5% water, 25.3% pork), were determined and these were evaluated against a full-fat commercial control (R4). Force values of R1 were not significantly different to R4, however, force values for R2 and R3 were lower (P<0.001). No significant differences were observed between R1, R3 and R4 for visual colour or sensory acceptability scores throughout the study, whereas scores for R2 were lower. Sensory analysis indicated that R2 had lower scores for texture (P<0.01), chewiness (P<0.01), acceptability (P<0.01), flavour (P<0.05) and preference (P<0.01). Results from this study suggest that it is possible to successfully replace pork meat with functional fish proteins in the manufacture of sausage type products.