Holmbuch0014

This review is focused on the description and discussion of the alterations of astrocytes and microglia interplay in models of Alzheimer's disease (AD). AD is an age-related neurodegenerative pathology with a slowly progressive and irreversible decline of cognitive functions. One of AD's histopathological hallmarks is the deposition of amyloid beta (Aβ) plaques in the brain. Long regarded as a non-specific, mere consequence of AD pathology, activation of microglia and astrocytes is now considered a key factor in both initiation and progression of the disease, and suppression of astrogliosis exacerbates neuropathology. Reactive astrocytes and microglia overexpress many cytokines, chemokines, and signaling molecules that activate or damage neighboring cells and their mutual interplay can result in virtuous/vicious cycles which differ in different brain regions. Heterogeneity of glia, either between or within a particular brain region, is likely to be relevant in healthy conditions and disease processes. Differential crosstalk between astrocytes and microglia in CA1 and CA3 areas of the hippocampus can be responsible for the differential sensitivity of the two areas to insults. Understanding the spatial differences and roles of glia will allow us to assess how these interactions can influence the state and progression of the disease, and will be critical for identifying therapeutic strategies.Trypanosoma cruzi dysregulates the gene expression profile of primary human cardiomyocytes (PHCM) during the early phase of infection through a mechanism which remains to be elucidated. The role that small non-coding RNAs (sncRNA) including PIWI-interacting RNA (piRNA) play in regulating gene expression during the early phase of infection is unknown. Tiragolumab To understand how T. cruzi dysregulate gene expression in the heart, we challenged PHCM with T. cruzi trypomastigotes and analyzed sncRNA, especially piRNA, by RNA-sequencing. The parasite induced significant differential expression of host piRNAs, which can target and regulate the genes which are important during the early infection phase. An average of 21,595,866 (88.40%) of clean reads mapped to the human reference genome. The parasite induced 217 unique piRNAs that were significantly differentially expressed (q ≥ 0.8). Of these differentially expressed piRNAs, 6 were known and 211 were novel piRNAs. In silico analysis showed that some of the dysregulated known and novel piRNAs could target and potentially regulate the expression of genes including NFATC2, FOS and TGF-β1, reported to play important roles during T. cruzi infection. Further evaluation of the specific functions of the piRNAs in the regulation of gene expression during the early phase of infection will enhance our understanding of the molecular mechanism of T. cruzi pathogenesis. Our novel findings constitute the first report that T. cruzi can induce differential expression of piRNAs in PHCM, advancing our knowledge about the involvement of piRNAs in an infectious disease model, which can be exploited for biomarker and therapeutic development.Weld bead geometry features (WBGFs) such as the bead width, height, area, and center of gravity are the common factors for weighing welding quality control. The effective modeling of these WBGFs contributes to implementing timely decision making of welding process parameters to improve welding quality and enhance automatic levels. In this work, a dynamic modeling method of WBGFs is presented based on machine vision and learning in multipass gas metal arc welding (GMAW) with typical joints. A laser vision sensing system is used to detect weld seam profiles (WSPs) during the GMAW process. A novel WSP extraction method is proposed using scale-invariant feature transform and machine learning. The feature points of the extracted WSP, namely the boundary points of the weld beads, are identified with slope mutation detection and number supervision. In order to stabilize the modeling process, a fault detection and diagnosis method is implemented with cubic exponential smoothing, and the diagnostic accuracy is within 1.50 pixels. A linear interpolation method is presented to implement sub pixel discrimination of the weld bead before modeling WBGFs. With the effective feature points and the extracted WSP, a scheme of modeling the area, center of gravity, and all-position width and height of the weld bead is presented. Experimental results show that the proposed method in this work adapts to the variable features of the weld beads in thick plate GMAW with T-joints and butt/lap joints. This work can provide more evidence to control the weld formation in a thick plate GMAW in real time.Type 2 diabetes mellitus (T2DM) has become a modern-day plague by reaching epidemic levels throughout the world. Due to its similar pathogenesis, gestational diabetes (GDM) increases in parallel to T2DM. The prevalence of T2DM (3.9-18.3%) and GDM (5.1-37.7%) in countries of the Arab Gulf are amongst the highest internationally, and they are still rising precipitously. This review traces the reasons among the Arab nations for (a) the surge of T2DM and GDM and (b) the failure to contain it. During the last five decades, the massive oil wealth in many Arab countries has led to the unhealthy lifestyle changes in physical activity and diet. The excess consumption of calories turned the advantageous genes, originally selected for the famine-like conditions, detrimental fueling obesity and insulin resistance. Despite genetic differences in these populations, GDM-a marker for future obesity and T2DM-can overcome this scourge of T2DM through active follow-up and screening after delivery. However, the health policies of most Arab countries have fallen short. Neglecting this unique chance will miss an irreplaceable opportunity to turn the tide of the T2DM and obesity epidemic in the Middle Eastern Arab Gulf countries-as well as globally.Polarization mode dispersion is recognized as a key factor limiting optical transmission systems, particularly those fiber links that run at bit rates beyond 10 Gbps. In-line test and characterization of polarization mode dispersion are thus of critical importance to evaluate the quality of installed optical fibers that are in use for high-speed signal traffics. However, polarization-based effects in optical fibers are stochastic and quite sensitive to a range of environmental changes, including optical cable movements. This, in turn, gives rise to undesired variations in light polarization that adversely impair the quality of the signal transmission in the link. In this work, we elaborate on experimental testing and theoretical analysis to asses changes of polarization mode dispersion in optical fibers that are caused by environmental variations, here wind gusts in particular. The study was performed on commercially harnessed optical fibers installed within optical power ground wire cables, taking into account different weather conditions.