The analysis of WIG20 stock index in R: a case study

In this short note we would like to show the basic methods of analyzing time series. This methods leads us to the different models of time series (decomposition, ARIMA, Fourier techniques, exponentially smoothing and GARCH). The correctness of the models obtained may be verified by behavior of residuals (small variance, stationary, uncorrelated, normally distributes) or by verifying the predictions. This second method not will be discussed here. We omit the lot of data mining methods, which may be applied to the stock index time series, such as neural networks and genetic algorithms.У представленій роботі коротко наведені методи аналізу часових рядів. Ці методи дозволяють розробити різноманітні моделі часових рядів (розкладання, ARIMA, метод Фур’є, експонентне згладжування та GARCH). Точність отриманих моделей можна перевірити за допомогою нев’язок (невеликі відхилення, стаціонарні, корелювання та некорелювання) або шляхом верифікації прогнозів (це не представлене у даному дописі). Також не розглядаються багато методів інтелектуального аналізу даних, які можуть бути застосовані до фондового індексу часових рядів, наприклад, нейронні мережі та генетичні алгоритми.В данной работе коротко представлены методы анализа временных рядов. Эти методы позволяют разработать различные модели временных рядов (разложение, ARIMA, метод Фурье, сглаживание по экспоненте и GARCH). Точность полученных моделей можно проверить с помощью невязок (небольшие отклонения, стационарные, коррелированные и некоррелированные) или путем верификации прогнозов (что не будет здесь представлено). Мы опускаем также множество методов интеллектуального анализа данных, которые могут быть применены к фондовому индексу временных рядов, такие как нейронные сети и генетические алгоритмы

Disulfiram/copper selectively eradicates AML leukemia stem cells in vitro and in vivo by simultaneous induction of ROS-JNK and inhibition of NF-κB and Nrf2

© 2017 The Authors. Published by Nature Publishing Group. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1038/cddis.2017.176Acute myeloid leukemia (AML) is a heterogeneous malignancy. Despite the advances in past decades, the clinical outcomes of AML patients remain poor. Leukemia stem cells (LSCs) is the major cause of the recurrence of AML even after aggressive treatment making, promoting development of LSC-targeted agents is an urgent clinical need. Although the antitumor activity of disulfiram (DS), an approved anti-alcoholism drug, has been demonstrated in multiple types of tumors including hematological malignancies such as AML, it remains unknown whether this agent would also be able to target cancer stem cells like LSCs. Here, we report the in vitro and in vivo activity of DS in combination with copper (Cu) against CD34(+)/CD38(+) leukemia stem-like cells sorted from KG1α and Kasumi-1 AML cell lines, as well as primary CD34(+) AML samples. DS plus Cu (DS/Cu) displayed marked inhibition of proliferation, induction of apoptosis, and suppression of colony formation in cultured AML cells while sparing the normal counterparts. DS/Cu also significantly inhibited the growth of human CD34(+)/CD38(+) leukemic cell-derived xenografts in NOD/SCID mice. Mechanistically, DS/Cu-induced cytotoxicity was closely associated with activation of the stress-related ROS-JNK pathway as well as simultaneous inactivation of the pro-survival Nrf2 and nuclear factor-κB pathways. In summary, our findings indicate that DS/Cu selectively targets leukemia stem-like cells both in vitro and in vivo, thus suggesting a promising LSC-targeted activity of this repurposed agent for treatment of relapsed and refractory AML

Fibroblast growth factor signalling controls nervous system patterning and pigment cell formation in Ciona intestinalis

During the development of the central nervous system (CNS), combinations of transcription factors and signalling molecules orchestrate patterning, specification and differentiation of neural cell types. In vertebrates, three types of melanin-containing pigment cells, exert a variety of functional roles including visual perception. Here we analysed the mechanisms underlying pigment cell specification within the CNS of a simple chordate, the ascidian Ciona intestinalis. Ciona tadpole larvae exhibit a basic chordate body plan characterized by a small number of neural cells. We employed lineage-specific transcription profiling to characterize the expression of genes downstream of fibroblast growth factor signalling, which govern pigment cell formation. We demonstrate that FGF signalling sequentially imposes a pigment cell identity at the expense of anterior neural fates. We identify FGF-dependent and pigment cell-specific factors, including the small GTPase, Rab32/38 and demonstrated its requirement for the pigmentation of larval sensory organs

Preconditioning with Physiological Levels of Ethanol Protect Kidney against Ischemia/Reperfusion Injury by Modulating Oxidative Stress

Oxidative stress due to excessive production of reactive oxygen species (ROS) and subsequent lipid peroxidation plays a critical role in renal ischemia/reperfusion (IR) injury. The purpose of current study is to demonstrate the effect of antecedent ethanol exposure on IR-induced renal injury by modulation of oxidative stress.Bilateral renal warm IR was induced in male C57BL/6 mice after ethanol or saline administration. Blood ethanol concentration, kidney function, histological damage, inflammatory infiltration, cytokine production, oxidative stress, antioxidant capacity and Aldehyde dehydrogenase (ALDH) enzymatic activity were assessed to evaluate the impact of antecedent ethanol exposure on IR-induced renal injury.After bilateral kidney ischemia, mice preconditioned with physiological levels of ethanol displayed significantly preserved renal function along with less histological tubular damage as manifested by the reduced inflammatory infiltration and cytokine production. Mechanistic studies revealed that precondition of mice with physiological levels of ethanol 3 h before IR induction enhanced antioxidant capacity characterized by significantly higher superoxidase dismutase (SOD) activities. Our studies further demonstrated that ethanol pretreatment specifically increased ALDH2 activity, which then suppressed lipid peroxidation by promoting the detoxification of Malondialdehyde (MDA) and 4-hydroxynonenal (HNE).Our results provide first line of evidence indicating that antecedent ethanol exposure can provide protection for kidneys against IR-induced injury by enhancing antioxidant capacity and preventing lipid peroxidation. Therefore, ethanol precondition and ectopic ALDH2 activation could be potential therapeutic approaches to prevent renal IR injury relevant to various clinical conditions

On the class of g-monotone dependence functions

In this paper a higher class of monotone dependence functions is defined and their properties are investigated. A class of monotone dependence functions is introduced in Kowalczyk (1987) and Kowalczyk et al. (1977). Another, one parameter class is considered in Krajka et al. (1992). The higher class of monotone dependence functions described in this paper generalizes both these cases. The paper is complemented by examples and applications.Monotone dependence functions Measures of dependence Quantile Independent, Positively (negatively) quadrant dependent random variables

Necessary and sufficient conditions for weak convergence of random sums of independent random variables

summary:Let $\{X_n,\, n\geq 1\}$ be a sequence of independent random variables such that $EX_n=a_n$, $E(X_n-a_n)^2=\sigma _n^2$, $n\geq 1$. Let $\{N_n,\, n\geq 1\}$ be a sequence od positive integer-valued random variables. Let us put $S_{N_n}=\sum_{k=1}^{N_n} X_k$, $L_n=\sum_{k=1}^{n} a_k$, $s_n^2=\sum_{k=1}^{n} \sigma _k^2$, $n\geq 1$. In this paper we present necessary and sufficient conditions for weak convergence of the sequence $\{(S_{N_n}-L_n)/s_n,\, n\geq 1\}$, as $n\rightarrow \infty$. The obtained theorems extend the main result of M. Finkelstein and H.G. Tucker (1989)

Oszacowanie Qα na podstawie eksperymentalnie wyznaczonych mas i innych własności jąder atomowych

The specially interesting experimental value, in the nuclear physic, describing the alpha decay is the decay energy Qα. This energy is a key to understanding the series of nuclei disorders. On the basis of decay energy we may compute sequential masses and energy of unstable nuclides. Because alpha is the helium element, thus from a nucleus with N neutrons and Z protons after the alpha decay we obtain a nucleus with N-2 and Z-2 protons and neutrons, respectively. It is natural to compute Qα as a difference between the mass of nuclei with N neutrons and Z protons and masses obtained after decay i.e. the mass of nuclei with N-2 neutrons and Z-2 protons and the mass of helium element. We tested this known “classical“ formula based on a large collection of the newest experimental data, the so called AME2012 and NUBASE2012 data bases. We computed accurate constants in the “classical” formula. Additionally, we showed inadequacy of the “classical” model. The almost three times better model is the one based on a neutral network (named in paper MSN) but we prefer slightly better (in comparison with MSN) the nonlinear regression model (named MQT). MQT is the development of the “classical” method taking additionally into account the terms with separation energy neutrons and protons multiplied by multinomials of numbers of neutrons N and protons Z, respectively. In the paper we show how the mentioned above methods may be used to prediction of unknown values of Qα. All computations were made in language R.Szczególnie interesującą wielkością w fizyce jądrowej jest energia rozpadu cząstki alfa. Wielkość ta umożliwia odtworzenie mas i energii jąder szybko zmieniających się w przemianach jądrowych pierwiastków. Ponieważ cząstka alfa jest jądrem atomu helu, więc z jądra o N neutronach i Z protonach otrzymujemy po przemianie jądro o N-2 neutronach i Z-2 protonach oraz jądro atomu helu. Dlatego naturalne jest szacowanie energii Qα jako różnicy mas jądra przed przemianą i jądra po przemianie wraz z masą atomu helu. Jest to tzw. “klasyczny” sposób obliczania energii Qα. Na podstawie dużego zbioru nowo uzyskanych eksperymentalnych wyników (bazy danych AME2012 I NUBASE2012) chcielibyśmy w tej pracy zweryfikować “klasyczny” sposób obliczania Qα. Obliczymy dokładniej stałe występujące w “klasycznym” wzorze a potem pokażemy, że niektóre inne metody dają zdecydowanie mniejszy błąd niż wspomniana “klasyczna” metoda. W szczególności opiszemy sieci neuronowe (MSN) oraz przedstawimy preferowaną przez nas metodę MQT opartą na nieliniowej regresji. MQT może być traktowana jako rozwinięcie “klasycznej” metody poprzez uwzględnieni dodatkowo członów z energiami separacji protonów i neutronów pomnożonych przez odpowiednie wielomiany od liczby protonów i neutronów. Dodatkowo pokażemy jak te wszystkie metody służą do prognozowania nieznanych wartości Qα. Wszystkie obliczenia wykonaliśmy w języku R