Relationship of cow and calf circulating lipidomes with colostrum lipid composition and metabolic status of the cow

Newborn calves rely on lipids in colostrum for energy and immune function. The lipid concentration in colostrum, however, is highly variable, and little is known about its composition and maternal factors that influence its composition. The first objective was to measure plasma lipid composition of multiparous cows at 35 d before calving (BC; 35 ± 3 d; ± standard deviation) and 7 d BC (7 ± 2 d), their colostrum, and serum lipid composition of calves (24 h after birth) using multiple reaction monitoring profiling, which is an exploratory and highly sensitive lipidomic analysis method that screens lipids based on chemical functionality. Second, data were analyzed to determine if there were relationships between circulating lipids in the cow, colostrum lipids, and calf serum lipids. Third, relationships between markers of metabolic status of the cows and circulating and colostrum lipids were analyzed with correlation analysis. Blood was sampled and plasma prepared from multiparous cows (n = 16) at 35 and 7 d BC. Within 3 h of parturition, colostrum was collected from cows and fed to her calf. Calves received another feeding of colostrum within 12 h after birth and a serum sample was collected from each calf 24 h after the first feeding of colostrum. The metabolic status of cows was evaluated using insulin, glucose, and nonesterified fatty acid area under the curve in response to an intravenous glucose tolerance test performed at 3 wk BC. Lipids were extracted from plasma, colostrum, and calf serum and were analyzed using multiple reaction monitoring profiling. Concentration of lipids were calculated using spiked in standards and expressed as percent of lipids identified. Data were uploaded into MetaboAnalyst 5.0 for multivariate and univariate analysis. Principal component analysis indicated that circulating lipids in the cow and calf were distinct from lipids in colostrum. Phosphatidylglycerol (PG) concentration was greater in colostrum and calf serum than in cow plasma, with 23 of the 24 PG found in colostrum also found in calf serum. In response to intravenous glucose tolerance test in late gestation, nonesterified fatty acid area under the curve was positively related to total triacylglycerols lipids in 7 d BC plasma (r = 0.63) but negatively related to total membrane lipids in colostrum (r = ?0.55). Thus, the metabolic status of the dam influences circulating lipids and colostrum lipid content. Moreover, the circulating lipidome of the cow and calf are similar to one another and distinct from the colostrum lipidome, except for PG, where it appears that colostrum serves as the source for PG in the calf's circulation.     

High-Fat Diet Aggravates Cerebral Infarct,Hemorrhagic Transformation and Neuroinflammation in a Mouse Stroke Model

Background: Stroke in context of type 2 diabetes (T2D) is associated with a poorer outcome than in non-diabetic conditions. We aimed at creating a new reproducible mouse model of stroke in impaired glucose tolerance conditions induced by high-fat diet. Methods: Adult C57BL6 mice were fed for 2 months with either normal diet (ND) or high-fat diet (HFD). We used a model of Middle Cerebral Artery Occlusion (MCAO) for 90 min. Oral Glucose Tolerance Test (OGTT) and Insulin Tolerance Test (ITT) were used to assess pre-diabetic status. Brain infarct volume, hemorrhagic transformation (HT) as well as systemic and cerebral inflammatory markers were evaluated. Results: HFD was associated with an increased body weight and glycemia following OGTT. The HFD group presented a significant increase in brain infarct volume (38.7 (IQR 30–46.7%) vs. 28.45 (IQR 21–30%); p = 0.016) and HT (HFD: 2 (IQR 1–5) vs. ND: 0 (IQR 0–1); p = 0.012) and higher levels of IL-6 and MCP-1 in infarcted hemisphere compared to the ND group. Conclusion: Two months of HFD in adult mice were sufficient to alter the lipid profile and the control of hyperglycemia. These metabolic perturbations were significantly associated with increased infarct volume and hemorrhagic complications.     

Knowledge-Based Virtual Modeling and Simulation of Manufacturing Processes for Industry 4.0

Abstract

Industry 4.0 aims at providing a digital representation of a production landscape, but the challenges in building, maintaining, optimizing, and evolving digital models in inter-organizational production chains have not been identified yet in a systematic manner. In this paper, various Industry 4.0 research and technical challenges are addressed, and their present scenario is discussed. Moreover, in this article, the novel concept of developing experience-based virtual models of engineering entities, process, and the factory is presented. These models of production units, processes, and procedures are accomplished by virtual engineering object (VEO), virtual engineering process (VEP), and virtual engineering factory (VEF), using the knowledge representation technique of Decisional DNA. This blend of the virtual and physical domains permits monitoring of systems and analysis of data to foresee problems before they occur, develop new opportunities, prevent downtime, and even plan for the future by using simulations. Furthermore, the proposed virtual model concept not only has the capability of Query Processing and Data Integration for Industrial Data but also real-time visualization of data stream processing.     

Models for circular data from time series spectra

Circular data are those for which the natural support is the unit circle and its toroidal extensions. Numerous constructions have been proposed which can be used to generate models for such data. We propose a new, very general, one based on the normalization of the spectra of complex-valued stationary processes. As illustrations of the new construction's application, we study models for univariate circular data obtained from the spectra of autoregressive moving average models and relate them to existing models in the literature. We also propose and investigate multivariate circular models obtained from the high-order spectra of stationary stochastic processes generated using linear filtering with an autoregressive moving average response function. A new family of distributions for a Markov process on the circle is also introduced. Results for asymptotically optimal inference for dependent observations on the circle are presented which provide a new paradigm for inference with circular models. The application of one of the new families of spectra-generated models is illustrated in an analysis of wind direction data.     

Alteration of the Route to Menaquinone towards Isochorismate-Derived Metabolites

Chorismate and isochorismate constitute branch-point intermediates in the biosynthesis of many aromatic metabolites in microorganisms and plants. To obtain unnatural compounds, we modified the route to menaquinone in Escherichia coli. We propose a model for the binding of isochorismate to the active site of MenD ((1R,2S, 5S,6S)-2-succinyl-5-enolpyruvyl-6-hydroxycyclohex-3-ene-1-carboxylate (SEPHCHC) synthase) that explains the outcome of the native reaction with α-ketoglutarate. We have rationally designed variants of MenD for the conversion of several isochorismate analogues. The double-variant Asn117Arg–Leu478Thr preferentially converts (5S,6S)-5,6-dihydroxycyclohexa-1,3-diene-1-carboxylate (2,3-trans-CHD), the hydrolysis product of isochorismate, with a >70-fold higher ratio than that for the wild type. The single-variant Arg107Ile uses (5S,6S)-6-amino-5-hydroxycyclohexa-1,3-diene-1-carboxylate (2,3-trans-CHA) as substrate with >6-fold conversion compared to wild-type MenD. The novel compounds have been made accessible in vivo (up to 5.3 g L⁻¹). Unexpectedly, as the identified residues such as Arg107 are highly conserved (>94 %), some of the designed variations can be found in wild-type SEPHCHC synthases from other bacteria (Arg107Lys, 0.3 %). This raises the question for the possible natural occurrence of as yet unexplored branches of the shikimate pathway.     

TiO2/MXene-Assisted LDI-MS for Urine Metabolic Profiling in Urinary Disease

Cancer remains an intractable medical problem. Rapid diagnosis and identification of cancer are critical to differentiate it from nonmalignant diseases. High-throughput biofluid metabolic analysis has potential for cancer diagnosis. Nevertheless, the present metabolite analysis method does not meet the demand for high-throughput screening of diseases. Herein, a high-throughput, cost-effective, and noninvasive urine metabolic profiling method based on TiO₂/MXene-assisted laser desorption/ionization mass spectrometry (LDI-MS) is presented for the efficient screening of bladder cancer (BC) and nonmalignant urinary disease. Combined with machine learning, TiO₂/MXene-assisted LDI-MS enables high diagnostic accuracy (96.8%) for the classification of patient groups (including 47 BC and 46 ureteral calculus (UC) patients) from healthy controls (113 cases). In addition, BC patients can also be identified from noncancerous UC individuals with an accuracy of 88.3% in the independent test cohort. Furthermore, metabolite variations between BC and UC individuals are investigated based on relative quantification, and related pathways are also discussed. These results suggest that this method, based on urine metabolic patterns, provides a potential tool for rapidly distinguishing urinary diseases and it may pave the way for precision medicine.     

SiC/SiC mini-composites with multilayer ZrSiO4 interphase: Room-temperature properties and toughening mechanism

SiC/SiC mini-composites reinforced with SiC fibers coated with different numbers of ZrSiO₄ sublayers prepared via a non-hydrolytic sol-gel process were fabricated. The tensile strength and work of fracture of the prepared SiC/SiC mini-composites were determined, and the relationship between their mechanical properties and fracture morphologies was discussed. The toughening mechanism and the variation tendency of their mechanical properties were further elaborated by analyzing the interfacial debonding morphologies of the SiC/SiC mini-composites with 1 and 4 layers of ZrSiO₄ interphase as well as the results of prior studies. A relatively rare phenomenon—the delamination of the multilayer ZrSiO₄ interphase in the SiC/SiC mini-composites but not on the SiC fibers—was observed, which clearly demonstrated the weak bonding between the ZrSiO₄ sublayers in the SiC/SiC mini-composites. The ZrSiO₄ sublayer delamination mechanism was then explained based on the high-magnification morphologies found in and beside the ZrSiO₄ interphase.