Two-Stage Method Based on Local Polynomial Fitting for a Linear Heteroscedastic Regression Model and Its Application in Economics

We introduce the extension of local polynomial fitting to the linear heteroscedastic regression model. Firstly, the local polynomial fitting is applied to estimate heteroscedastic function, then the coefficients of regression model are obtained by using generalized least squares method. One noteworthy feature of our approach is that we avoid the testing for heteroscedasticity by improving the traditional two-stage method. Due to nonparametric technique of local polynomial estimation, we do not need to know the heteroscedastic function. Therefore, we can improve the estimation precision, when the heteroscedastic function is unknown. Furthermore, we focus on comparison of parameters and reach an optimal fitting. Besides, we verify the asymptotic normality of parameters based on numerical simulations. Finally, this approach is applied to a case of economics, and it indicates that our method is surely effective in finite-sample situations

Local Polynomial Regression Solution for Differential Equations with Initial and Boundary Values

Numerical solutions of the linear differential boundary issues are obtained by using a local polynomial estimator method with kernel smoothing. To achieve this, a combination of a local polynomial-based method and its differential form has been used. The computed results with the use of this technique have been compared with the exact solution and other existing methods to show the required accuracy of it. The effectiveness of this method is verified by three illustrative examples. The presented method is seen to be a very reliable alternative method to some existing techniques for such realistic problems. Numerical results show that the solution of this method is more accurate than that of other methods

Introduction of modern diagnostic approach to detect Babesia in clinical and animal samples

Babezija je parazit, ki se s klopom prenese na ljudi in živali, kjer lahko povzroči okužbo. Zlati standard dokazovanja babezioze je neposredni mikroskopski pregled barvanega krvnega razmaza, s katerimi ne moremo določiti babezije do vrste natančno. Babeziozo lahko dokažemo tudi z metodo posredne imunofluorescence, ki pa ni primerna pri imunsko oslabljenih bolnikih. Z magistrsko nalogo smo razvili PCR v realnem času za dokaz DNA babezij, ki povzročajo okužbe pri ljudeh in živalih v Sloveniji in s tem olajšali ter skrajšali čas do laboratorijskega izvida. Dokazali smo, da je metoda PCR v realnem času bolj občutljiva in bolj specifična od neposrednega mikroskopskega pregleda preparata krvi ter klasičnega PCR. Kot selekcijski marker smo uporabili gen 18S rRNA, ki vsebuje hipervariabilne odseke, obdane z visoko ohranjenimi regijami. Razvili smo visoko specifičen in občutljiv PCR v realnem času, ki pomnožuje sev humane babezije Babesia sp. Irk, ki so ga dokazali leta 2014 pri imunsko oslabljeni bolnici iz Prekmurja. S kvantifikacijo z digitalnim PCR smo spremljali potek parazitemije in zdravljenja pri bolnici ter dokazali babezijsko DNA tudi po 89. dneh zdravljenja, ko so bili rezultati ostalih metod že negativni. Zaključimo lahko, da je PCR v realnem času hitra, visoko občutljiva in enostavna metoda, ki omogoča dokaz babezioze v zgodnjih fazah bolezni ter spremljanje poteka zdravljenja.Babesia is a parasite that can be transmitted to humans and animals, where it causes infection. With methods like microscopic staining of blood smears, that do not give us the information about the species, and indirect immunofluorescence, that we can not use on immunocompromised patients, real time PCR seems to be a much better choice for diagnostics. Within M. Sc. Thesis we developed real time PCR for detection of Babesia species DNA, found in humans and animals around Slovenia. We proved that real time PCR is a more sensitive and specific method than the microscopic staining of blood smears and conventional PCR. As a selection marker we used 18S rRNA gene with hipervariable sections that are surrounded with highly conservative regions. Our real time PCR amplifies strain of human Babesia sp. Irk, that was first found in 2014 in an immunocompromised patient from Prekmurje. By using absolute quantification of a digital PCR, we were able to follow parasitemia and treatment of the patient and detected DNA of the parasite even after 89 days from the beginning of the treatment, when all the other methods showed negative results. In conclusion, we can say that real time PCR is a quick, highly sensitive method that is easy to use and is useful for detection of babesial DNA at the beginning of the infection as well as for monitoring the course of treatment

Radioprotective Effect of Grape Seed Proanthocyanidins In Vitro and In Vivo

We have demonstrated that grape seed proanthocyanidins (GSPs) could effectively scavenge hydroxyl radical (•OH) in a dose-dependent manner. Since most of the ionizing radiation- (IR-) induced injuries were caused by •OH, this study was to investigate whether GSPs would mitigate IR-induced injuries in vitro and in vivo. We demonstrated that GSPs could significantly reduce IR-induced DNA strand breaks (DSBs) and apoptosis of human lymphocyte AHH-1 cells. This study also showed that GSPs could protect white blood cells (WBC) from IR-induced injuries, speed up the weight of mice back, and decrease plasma malondialdehyde (MDA), thus improving the survival rates of mice after ionizing radiation. It is suggested that GSPs have a potential as an effective and safe radioprotective agent

Protective Effects of Hydrogen against Low-Dose Long-Term Radiation-Induced Damage to the Behavioral Performances, Hematopoietic System, Genital System, and Splenic Lymphocytes in Mice

Molecular hydrogen (H2) has been previously reported playing an important role in ameliorating damage caused by acute radiation. In this study, we investigated the effects of H2 on the alterations induced by low-dose long-term radiation (LDLTR). All the mice in hydrogen-treated or radiation-only groups received 0.1 Gy, 0.5 Gy, 1.0 Gy, and 2.0 Gy whole-body gamma radiation, respectively. After the last time of radiation exposure, all the mice were employed for the determination of the body mass (BM) observation, forced swim test (FST), the open field test (OFT), the chromosome aberration (CA), the peripheral blood cells parameters analysis, the sperm abnormality (SA), the lymphocyte transformation test (LTT), and the histopathological studies. And significant differences between the treatment group and the radiation-only groups were observed, showing that H2 could diminish the detriment induced by LDLTR and suggesting the protective efficacy of H2 in multiple systems in mice against LDLTR

Crystal structure of rhodopsin bound to arrestin by femtosecond X-ray laser.

G-protein-coupled receptors (GPCRs) signal primarily through G proteins or arrestins. Arrestin binding to GPCRs blocks G protein interaction and redirects signalling to numerous G-protein-independent pathways. Here we report the crystal structure of a constitutively active form of human rhodopsin bound to a pre-activated form of the mouse visual arrestin, determined by serial femtosecond X-ray laser crystallography. Together with extensive biochemical and mutagenesis data, the structure reveals an overall architecture of the rhodopsin-arrestin assembly in which rhodopsin uses distinct structural elements, including transmembrane helix 7 and helix 8, to recruit arrestin. Correspondingly, arrestin adopts the pre-activated conformation, with a ∼20° rotation between the amino and carboxy domains, which opens up a cleft in arrestin to accommodate a short helix formed by the second intracellular loop of rhodopsin. This structure provides a basis for understanding GPCR-mediated arrestin-biased signalling and demonstrates the power of X-ray lasers for advancing the frontiers of structural biology

Estimation for a Second-Order Jump Diffusion Model from Discrete Observations: Application to Stock Market Returns

This paper proposes a second-order jump diffusion model to study the jump dynamics of stock market returns via adding a jump term to traditional diffusion model. We develop an appropriate maximum likelihood approach to estimate model parameters. A simulation study is conducted to evaluate the performance of the estimation method in finite samples. Furthermore, we consider a likelihood ratio test to identify the statistically significant presence of jump factor. The empirical analysis of stock market data from North America, Asia, and Europe is provided for illustration