Tauopathy is a pathological hallmark of many neurodegenerative diseases. It is characterized by abnormal aggregates of pathological phosphotau and somatodendritic redistribution. One suggested strategy for treating tauopathy is to stimulate autophagy, hence, getting rid of these pathological protein aggregates. One key controller of autophagy is mTOR. Since stimulation of mTOR leads to inhibition of autophagy, inhibitors of mTOR will cause stimulation of autophagy process. In this report, tauopathy was induced in mice using annonacin. Blocking of mTOR was achieved through stereotaxic injection of siRNA against mTOR. The behavioral and immunohistochemical evaluation revealed the development of tauopathy model as proven by deterioration of behavioral performance in open field test and significant tau aggregates in annonacin-treated mice. Blocking of mTOR revealed significant clearance of tau aggregates in the injected side; however, tau expression was not affected by mTOR blockage.
The power system always has several variations in its profile due to random load changes or environmental effects such as device switching effects when generating further transients. Thus, an accurate mathematical model is important because most system parameters vary with time. Curve modeling of power generation is a significant tool for evaluating system performance, monitoring and forecasting. Several numerical techniques compete to fit the curves of empirical data such as wind, solar, and demand power rates. This paper proposes a new modified methodology presented as a parametric technique to determine the system's modeling equations based on the Bode plot equations and the vector fitting (VF) algorithm by fitting the experimental data points. The modification is derived from the familiar VF algorithm as a robust numerical method. This development increases the application range of the VF algorithm for modeling not only in the frequency domain but also for all power curves. Four case studies are addressed and compared with several common methods. From the minimal RMSE, the results show clear improvements in data fitting over other methods. The most powerful features of this method is the ability to model irregular or randomly shaped data and to be applied to any algorithms that estimating models using frequency-domain data to provide state-space or transfer function for the model.
It is known that secondary hyperparathyroidism (SH) and particularly skeletal changes is a severe condition in chronic kidney disease (CKD). Sagliker syndrome (SS) is a very prominent feature in CKD including uglifying human face appearances, short stature, extremely severe maxillary and mandibulary changes, soft tissues in the mouth, teeth-dental abnormalities, finger tip changes and severe psychological problems.
Hypotheses explaining pathogenesis of secondary hyperparathyroidism (SH) in late and severe CKD as a unique entity called Sagliker syndrome (SS) are still unclear. This international study contains 60 patients from Turkey, India, Malaysia, China, Romania, Egypt, Tunisia, Taiwan, Mexico, Algeria, Poland, Russia, and Iran. We examined patients and first degree relatives for cytogenetic chromosomal abnormalities, calcium sensing receptor (Ca SR) genes in exons 2 and 3 abnormalities and GNAS1 genes mutations in exons 1, 4, 5, 7, 10, 13. Our syndrome could be a new syndrome in between SH, CKD, and hereditary bone dystrophies. We could not find chromosomal abnormalities in cytogenetics and on Ca SR gene exons 2 and 3. Interestingly, we did find promising missense mutations on the GNAS1 gene exons 1, 4, 10, 4. We finally thought that those catastrophic bone diseases were severe SH and its late treatments due to monetary deficiencies and iatrogenic mistreatments not started as early as possible. This was a sine qua non humanity task. Those brand new striking GNAS1 genes missense mutations have to be considered from now on for the genesis of SS.