Cutting Edge: Suppression of GM-CSF Expression in Murine and Human T Cells by IL-27

GM-CSF is a potent proinflammatory cytokine that plays a pathogenic role in the CNS inflammatory disease experimental autoimmune encephalomyelitis. As IL-27 alleviates experimental autoimmune encephalomyelitis, we hypothesized that IL-27 suppresses GM-CSF expression by T cells. We found that IL-27 suppressed GM-CSF expression in CD4+ and CD8+ T cells in splenocyte and purified T cell cultures. IL-27 suppressed GM-CSF in Th1, but not Th17, cells. IL-27 also suppressed GM-CSF expression by human T cells in nonpolarized and Th1- but not Th17-polarized PBMC cultures. In vivo, IL-27p28 deficiency resulted in increased GM-CSF expression by CNS-infiltrating T cells during Toxoplasma gondii infection. Although in vitro suppression of GM-CSF by IL-27 was independent of IL-2 suppression, IL-10 upregulation, or SOCS3 signaling, we observed that IL-27-driven suppression of GM-CSF was STAT1 dependent. Our findings demonstrate that IL-27 is a robust negative regulator of GM-CSF expression in T cells, which likely inhibits T cell pathogenicity in CNS inflammation.

Predicting organic acid concentration from UV/vis spectrometry measurements - A comparison of machine learning techniques

The concentration of organic acids in anaerobic digesters is one of the most critical parameters for monitoring and advanced control of anaerobic digestion processes. Thus, a reliable online-measurement system is absolutely necessary. A novel approach to obtaining these measurements indirectly and online using UV/vis spectroscopic probes, in conjunction with powerful pattern recognition methods, is presented in this paper. An UV/vis spectroscopic probe from S::CAN is used in combination with a custom-built dilution system to monitor the absorption of fully fermented sludge at a spectrum from 200 to 750 nm. Advanced pattern recognition methods are then used to map the non-linear relationship between measured absorption spectra to laboratory measurements of organic acid concentrations. Linear discriminant analysis, generalized discriminant analysis (GerDA), support vector machines (SVM), relevance vector machines, random forest and neural networks are investigated for this purpose and their performance compared. To validate the approach, online measurements have been taken at a full-scale 1.3-MW industrial biogas plant. Results show that whereas some of the methods considered do not yield satisfactory results, accurate prediction of organic acid concentration ranges can be obtained with both GerDA and SVM-based classifiers, with classification rates in excess of 87% achieved on test data.

A mirage of genes

This paper examines the structure of popular conceptions of the new genetics, and assesses why genetics has been so readily accepted in medicine and in the public discourse. Adapting Rene Dubos' classic analysis, Mirage of Health, we examine the new genetics by comparing it to Dubos' analysis of the structure and limits of germ theory. Germ theory focuses on the internal rather than the external environment, emphasises a doctrine of specific aetiology, and adopts the metaphor of the body as a machine. The germ theory model narrowed our vision about disease aetiology, proved misleading in some cases, yet remained the basis for clinical medical models of disease. In recent years, genetics has moved to the cutting edge of medical research and thinking about disease and behaviour. The structure of popular conceptions of the new genetics shows remarkable parallels with germ theory. This has eased the acceptance of genetics but simultaneously raises questions about these genetic explanations. An appearance and allure of specificity privileges genetic explanations in the public discourse; on examination, this specificity may prove to be a mirage.

Kinematic Analysis and Dimensional Synthesis of Exechon Parallel Kinematic Machine for Large Volume Machining

A parallel kinematic machine (PKM) topology can only give its best performance when its geometrical parameters are optimized. In this paper, dimensional synthesis of a newly developed PKM is presented for the first time. An optimization method is developed with the objective to maximize both workspace volume and global dexterity of the PKM. Results show that the method can effectively identify design parameter changes under different weighted objectives. The PKM with optimized dimensions has a large workspace to footprint ratio and a large well-conditioned workspace, hence justifies its suitability for large volume machining.

Anisotropy of single crystal 3C-SiC during nanometric cutting

3C–SiC (the only polytype of SiC that resides in a diamond cubic lattice structure) is a relatively new material that exhibits most of the desirable engineering properties required for advanced electronic applications. The anisotropy exhibited by 3C–SiC during its nanometric cutting is significant, and the potential for its exploitation has yet to be fully investigated. This paper aims to understand the influence of crystal anisotropy of 3C–SiC on its cutting behaviour. A molecular dynamics simulation model was developed to simulate the nanometric cutting of single-crystal 3C–SiC in nine (9) distinct combinations of crystal orientations and cutting directions, i.e. (1?1?1) <-1?1?0>, (1?1?1) <-2?1?1>, (1?1?0) <-1?1?0>, (1?1?0) <0?0?1>, (1?1?0) <1?1?-2>, (0?0?1) <-1?1?0>, (0?0?1) <1?0?0>, (1?1?-2) <1?-1?0> and (1?-2?0) <2?1?0>.

In order to ensure the reliability of the simulation results, two separate simulation trials were carried out with different machining parameters. In the first trial, a cutting tool rake angle of -25°, d/r (uncut chip thickness/cutting edge radius) ratio of 0.57 and cutting velocity of 10 m s-1 were used whereas a second trial was done using a cutting tool rake angle of -30°, d/r ratio of 1 and cutting velocity of 4 m s-1. Both the trials showed similar anisotropic variation.

The simulated orthogonal components of thrust force in 3C–SiC showed a variation of up to 45%, while the resultant cutting forces showed a variation of 37%. This suggests that 3C–SiC is highly anisotropic in its ease of deformation. These results corroborate with the experimentally observed anisotropic variation of 43.6% in Young's modulus of 3C–SiC. The recently developed dislocation extraction algorithm (DXA) [1, 2] was employed to detect the nucleation of dislocations in the MD simulations of varying cutting orientations and cutting directions. Based on the overall analysis, it was found that 3C–SiC offers ease of deformation on either (1?1?1) <-1?1?0>, (1?1?0) <0?0?1>, or (1?0?0) <1?0?0> setups.

Molecular dynamics simulation model for the quantitative assessment of tool wear during single point diamond turning of cubic silicon carbide

Silicon carbide (SiC) is a material of great technological interest for engineering applications concerning hostile environments where silicon-based components cannot work (beyond 623 K). Single point diamond turning (SPDT) has remained a superior and viable method to harness process efficiency and freeform shapes on this harder material. However, it is extremely difficult to machine this ceramic consistently in the ductile regime due to sudden and rapid tool wear. It thus becomes non trivial to develop an accurate understanding of tool wear mechanism during SPDT of SiC in order to identify measures to suppress wear to minimize operational cost.

In this paper, molecular dynamics (MD) simulation has been deployed with a realistic analytical bond order potential (ABOP) formalism based potential energy function to understand tool wear mechanism during single point diamond turning of SiC. The most significant result was obtained using the radial distribution function which suggests graphitization of diamond tool during the machining process. This phenomenon occurs due to the abrasive processes between these two ultra hard materials. The abrasive action results in locally high temperature which compounds with the massive cutting forces leading to sp3–sp2 order–disorder transition of diamond tool. This represents the root cause of tool wear during SPDT operation of cubic SiC. Further testing led to the development of a novel method for quantitative assessment of the progression of diamond tool wear from MD simulations.

Brittle-ductile transition during diamond turning of single crystal silicon carbide

In this experimental study, diamond turning of single crystal 6H-SiC was performed at a cutting speed of 1 m/s on an ultra-precision diamond turning machine (Moore Nanotech 350 UPL) to elucidate the microscopic origin of ductile-regime machining. Distilled water (pH value 7) was used as a preferred coolant during the course of machining in order to improve the tribological performance. A high magnification scanning electron microscope (SEM FIB- FEI Quanta 3D FEG) was used to examine the cutting tool before and after the machining. A surface finish of Ra=9.2 nm, better than any previously reported value on SiC was obtained. Also, tremendously high cutting resistance was offered by SiC resulting in the observation of significant wear marks on the cutting tool just after 1 km of cutting length. It was found out through a DXR Raman microscope that similar to other classical brittle materials (silicon, germanium, etc.) an occurrence of brittle-ductile transition is responsible for the ductile-regime machining of 6H-SiC. It has also been demonstrated that the structural phase transformations associated with the diamond turning of brittle materials which are normally considered as a prerequisite to ductile-regime machining, may not be observed during ductile-regime machining of polycrystalline materials.

The development of a surface defect machining method for hard turning processes

Hard turning (HT) is a material removal process employing a combination of a single point cutting tool and high speeds to machine hard ferrous alloys which exhibit hardness values over 45 HRC. In this paper, a surface defect machining (SDM) method for HT is proposed which harnesses the combined advantages of porosity machining and pulsed laser pre-treatment processing. From previous experimental work, this was shown to provide better controllability of the process and improved quality of the machined surface. While the experiments showed promising results, a comprehensive understanding of this new technique could only be achieved through a rigorous, in depth theoretical analysis. Therefore, an assessment of the SDM technique was carried out using both finite element method (FEM) and molecular dynamics (MD) simulations.
FEM modelling was used to compare the conventional HT of AISI 4340 steel (52 HRC) using an Al2O3 insert with the proposed SDM method. The simulations showed very good agreement with the previously published experimental results. Compared to conventional HT, SDM provided favourable machining outcomes, such as reduced shear plane angle, reduced average cutting forces, improved surface roughness, lower residual stresses on the machined surface, reduced tool–chip interface contact length and increased chip flow velocity. Furthermore, a scientific explanation of the improved surface finish was revealed using a state-of-the-art MD simulation model which suggested that during SDM, a combination of both the cutting action and rough polishing action help improve the machined surface finish.

Shear instability of nanocrystalline silicon carbide during nanometric cutting

The shear instability of the nanoscrystalline 3C-SiC during nanometric cutting at a cutting speed of 100?m/s has been investigated using molecular dynamics simulation. The deviatoric stress in the cutting zone was found to cause sp3-sp2 disorder resulting in the local formation of SiC-graphene and Herzfeld-Mott transitions of 3C-SiC at much lower transition pressures than that required under pure compression. Besides explaining the ductility of SiC at 1500?K, this is a promising phenomenon in general nanoscale engineering of SiC. It shows that modifying the tetrahedral bonding of 3C-SiC, which would otherwise require sophisticated pressure cells, can be achieved more easily by introducing non-hydrostatic stress conditions.