Is String Interaction the Origin of Quantum Mechanics?

String theory developed by demanding consistency with quantum mechanics. In this paper we wish to reverse the reasoning. We pretend open string field theory is a fully consistent definition of the theory - it is at least a self consistent sector. Then we find in its structure that the rules of quantum mechanics emerge from the non-commutative nature of the basic string joining/splitting interactions, thus deriving rather than assuming the quantum commutation rules among the usual canonical quantum variables for all physical systems derivable from open string field theory. Morally we would apply such an argument to M-theory to cover all physics. If string or M-theory really underlies all physics, it seems that the door has been opened to an understanding of the origins of quantum mechanics.Comment: 15 pages. More discussion in "Outlook" section in v

Gene Expression Meta-Analysis Reveals Concordance in Gene Activation, Pathway, and Cell-Type Enrichment in Dermatomyositis Target Tissues.

ObjectiveWe conducted a comprehensive gene expression meta-analysis in dermatomyositis (DM) muscle and skin tissues to identify shared disease-relevant genes and pathways across tissues.MethodsSix publicly available data sets from DM muscle and two from skin were identified. Meta-analysis was performed by first processing data sets individually then cross-study normalization and merging creating tissue-specific gene expression matrices for subsequent analysis. Complementary single-gene and network analyses using Significance Analysis of Microarrays (SAM) and Weighted Gene Co-expression Network Analysis (WGCNA) were conducted to identify genes significantly associated with DM. Cell-type enrichment was performed using xCell.ResultsThere were 544 differentially expressed genes (FC ≥ 1.3, q < 0.05) in muscle and 300 in skin. There were 94 shared upregulated genes across tissues enriched in type I and II interferon (IFN) signaling and major histocompatibility complex (MHC) class I antigen-processing pathways. In a network analysis, we identified eight significant gene modules in muscle and seven in skin. The most highly correlated modules were enriched in pathways consistent with the single-gene analysis. Additional pathways uncovered by WGCNA included T-cell activation and T-cell receptor signaling. In the cell-type enrichment analysis, both tissues were highly enriched in activated dendritic cells and M1 macrophages.ConclusionThere is striking similarity in gene expression across DM target tissues with enrichment of type I and II IFN pathways, MHC class I antigen-processing, T-cell activation, and antigen-presenting cells. These results suggest IFN-γ may contribute to the global IFN signature in DM, and altered auto-antigen presentation through the class I MHC pathway may be important in disease pathogenesis

Reporters of TCR signaling identify arthritogenic T cells in murine and human autoimmune arthritis.

How pathogenic cluster of differentiation 4 (CD4) T cells in rheumatoid arthritis (RA) develop remains poorly understood. We used Nur77-a marker of T cell antigen receptor (TCR) signaling-to identify antigen-activated CD4 T cells in the SKG mouse model of autoimmune arthritis and in patients with RA. Using a fluorescent reporter of Nur77 expression in SKG mice, we found that higher levels of Nur77-eGFP in SKG CD4 T cells marked their autoreactivity, arthritogenic potential, and ability to more readily differentiate into interleukin-17 (IL-17)-producing cells. The T cells with increased autoreactivity, nonetheless had diminished ex vivo inducible TCR signaling, perhaps reflective of adaptive inhibitory mechanisms induced by chronic autoantigen exposure in vivo. The enhanced autoreactivity was associated with up-regulation of IL-6 cytokine signaling machinery, which might be attributable, in part, to a reduced amount of expression of suppressor of cytokine signaling 3 (SOCS3)-a key negative regulator of IL-6 signaling. As a result, the more autoreactive GFPhi CD4 T cells from SKGNur mice were hyperresponsive to IL-6 receptor signaling. Consistent with findings from SKGNur mice, SOCS3 expression was similarly down-regulated in RA synovium. This suggests that despite impaired TCR signaling, autoreactive T cells exposed to chronic antigen stimulation exhibit heightened sensitivity to IL-6, which contributes to the arthritogenicity in SKG mice, and perhaps in patients with RA

Cross-Tissue Transcriptomic Analysis Leveraging Machine Learning Approaches Identifies New Biomarkers for Rheumatoid Arthritis

There is an urgent need to identify biomarkers for diagnosis and disease activity monitoring in rheumatoid arthritis (RA). We leveraged publicly available microarray gene expression data in the NCBI GEO database for whole blood (N=1,885) and synovial (N=284) tissues from RA patients and healthy controls. We developed a robust machine learning feature selection pipeline with validation on five independent datasets culminating in 13 genes: TNFAIP6, S100A8, TNFSF10, DRAM1, LY96, QPCT, KYNU, ENTPD1, CLIC1, ATP6V0E1, HSP90AB1, NCL and CIRBP which define the RA score and demonstrate its clinical utility: the score tracks the disease activity DAS28 (p = 7e-9), distinguishes osteoarthritis (OA) from RA (OR 0.57, p = 8e-10) and polyJIA from healthy controls (OR 1.15, p = 2e-4) and monitors treatment effect in RA (p = 2e-4). Finally, the immunoblotting analysis of six proteins on an independent cohort confirmed two proteins, TNFAIP6/TSG6 and HSP90AB1/HSP90

Achieving high quality surface of laminated glass-reinforced plastics during milling

Milling is one of the most common ways of workpiece machining, but obtaining a high quality surface of laminated composite materials is difficult due to their layered structure, high strength characteristics and low heat conductivity. This poses a problem of creating a milling technology that provides a high quality surface. This research investigates STEF -1 glass-fiber plastic with fine grain structure processed on the equipment with high cutting speed. The object of the research is roughness Ra as a quality criterion. Our glass-fiber plastic milling experiments demonstrate that the surface quality depends to a large extent on the cutting modes and the wear level of the tool cutting edge which is determined by the size of the wear bevel on the flank surface. The blade of the cutting tool is established to wear unevenly during glass-fiber plastic processing as it interacts with two different materials. We recommend the wear bevel on the flank surface to be less than 0.35 mm to ensure the high quality of the laminated composite material surface. The cutting modes should be within the following range: feed per tooth is 0.15 ÷ 0.17 mm/tooth, cutting depth is 0.5 ÷ 0.9 mm, cutting speed is above 45 m/s, with the cutting part of the tool being made of high-strength instrumental materials

Gene Expression Meta-Analysis Reveals Concordance in Gene Activation, Pathway, and Cell-Type Enrichment in Dermatomyositis Target Tissues.

ObjectiveWe conducted a comprehensive gene expression meta-analysis in dermatomyositis (DM) muscle and skin tissues to identify shared disease-relevant genes and pathways across tissues.MethodsSix publicly available data sets from DM muscle and two from skin were identified. Meta-analysis was performed by first processing data sets individually then cross-study normalization and merging creating tissue-specific gene expression matrices for subsequent analysis. Complementary single-gene and network analyses using Significance Analysis of Microarrays (SAM) and Weighted Gene Co-expression Network Analysis (WGCNA) were conducted to identify genes significantly associated with DM. Cell-type enrichment was performed using xCell.ResultsThere were 544 differentially expressed genes (FC ≥ 1.3, q < 0.05) in muscle and 300 in skin. There were 94 shared upregulated genes across tissues enriched in type I and II interferon (IFN) signaling and major histocompatibility complex (MHC) class I antigen-processing pathways. In a network analysis, we identified eight significant gene modules in muscle and seven in skin. The most highly correlated modules were enriched in pathways consistent with the single-gene analysis. Additional pathways uncovered by WGCNA included T-cell activation and T-cell receptor signaling. In the cell-type enrichment analysis, both tissues were highly enriched in activated dendritic cells and M1 macrophages.ConclusionThere is striking similarity in gene expression across DM target tissues with enrichment of type I and II IFN pathways, MHC class I antigen-processing, T-cell activation, and antigen-presenting cells. These results suggest IFN-γ may contribute to the global IFN signature in DM, and altered auto-antigen presentation through the class I MHC pathway may be important in disease pathogenesis

Senskin deformable silicone-elastomer sensors for structural health monitoring: assessment of strain sensitivity and correction for thermal expansion

Within the framework of SENSKIN EU project (grant No. 635844), we have developed a soft capacitive sensor using silicone dielectric elastomer for Structural health monitoring (SHM). This sensor has a thin layer of stretchable silicone dielectric film and soft silicone electrodes as the active layer, which transduces strain signal into the easy-monitored capacitance change. The sensor output is measured as a ration of the sensor’s capacitance to the known value of the reference capacitor. The capacitive output of the sensor showed a linear response upon stretching in the strain range of 4.5 % to 5.5% with a pre-strain of 5.0 %. The sensor output increased by 0.01 when the strain was increased by 1.0 %. The sensor was exposed to a temperature change from -35 oC to 55 oC (the supposed working temperature range) with a ramping of 0.2 oC/min and, as a result, it showed a linear temperature dependence behavior with a slope of -0.001 sensor output per oC. Therefore, with the help of the embedded Platinum-1000 temperature sensor, the thermal expansion effect on the capacitive output can be excluded from the actual strain-induced capacitance change. These results provide practical reference to the application of the silicon-elastomer sensor for the SHM systems

Ferroelectrets: Heterogenous polymer electrets with high piezoelectric sensitivity for transducers

Nowadays, the demand for advanced functional materials in transducer technology is growing rapidly. Piezoelectric materials transform mechanical variables (displacement or force) into electrical signals (charge or voltage) and vice versa. They are interesting from both fundamental and application points of view. Ferrooelectrets (also called piezoelectrets) are a relatively young group of piezo-, pyro- and ferroelectric materials. They exhibit ferroic behavior phenomenologically undistinguishable from that of traditional ferroelectrics, although the materials per se are essentially non-polar space-charge electrets with artificial macroscopic dipoles (i.e., internally charged cavities). A lot of work has been done on ferroelectrets and their applications up to now. In this paper, we review and discuss mostly the work done at University of Potsdam on the research and development of ferroelectrets. We will, however, also mention important results from other teams, and prospect the challenges and future progress trend of the field of ferroelectret research

Single-Cell RNA Sequencing of Tocilizumab-Treated Peripheral Blood Mononuclear Cells as an in vitro Model of Inflammation.

COVID-19 has posed a significant threat to global health. Early data has revealed that IL-6, a key regulatory cytokine, plays an important role in the cytokine storm of COVID-19. Multiple trials are therefore looking at the effects of Tocilizumab, an IL-6 receptor antibody that inhibits IL-6 activity, on treatment of COVID-19, with promising findings. As part of a clinical trial looking at the effects of Tocilizumab treatment on kidney transplant recipients with subclinical rejection, we performed single-cell RNA sequencing of comparing stimulated PBMCs before and after Tocilizumab treatment. We leveraged this data to create an in vitro cytokine storm model, to better understand the effects of Tocilizumab in the presence of inflammation. Tocilizumab-treated cells had reduced expression of inflammatory-mediated genes and biologic pathways, particularly amongst monocytes. These results support the hypothesis that Tocilizumab may hinder the cytokine storm of COVID-19, through a demonstration of biologic impact at the single-cell level