Curcumin Attenuated Neurotoxicity in Sporadic Animal Model of Alzheimer’s Disease

Alzheimer’s disease (AD) is one of the most common neurodegenerative diseases leading to dementia. Despite research efforts, currently there are no effective pharmacotherapeutic options for the prevention and treatment of AD. Recently, numerous studies highlighted the beneficial effects of curcumin (CUR), a natural polyphenol, in the neuroprotection. Especially, its dual antioxidant and anti-inflammatory properties attracted the interest of researchers. In fact, besides its antioxidant and anti-inflammatory properties, this biomolecule is not degraded in the intestinal tract. Additionally, CUR is able to cross the blood–brain barrier and could therefore to be used to treat neurodegenerative pathologies associated with oxidative stress, inflammation and apoptosis. The present study aimed to assess the ability of CUR to induce neuronal protective and/or recovery effects on a rat model of neurotoxicity induced by aluminum chloride (AlCl₃), which mimics the sporadic form of Alzheimer’s disease. Our results showed that treatment with CUR enhances pro-oxidant levels, antioxidant enzymes activities and anti-inflammatory cytokine production and decreases apoptotic cells in AlCl₃-exposed hippocampus rats. Additionally, histopathological analysis of hippocampus revealed the potential of CUR in decreasing the hallmarks in the AlCl₃-induced AD. We also showed that CUR post-treatment significantly improved the behavioral, oxidative stress and inflammation in AlCl₃-exposed rats. Taken together, our data presented CUR as a nutraceutical potential through its protective effects that are more interesting than recovery ones in sporadic model of AD.     

Organoclays from alkaline-treated acid-activated clays

The cetyltrimethylammonium hydroxide (C16TMAOH) solution was proposed for the preparation of organoclays. Montmorillonite clay was acid activated at different acid/clay (a/c) (in mass) ratios, then treated with alkaline (sodium hydroxide) solution before being reacted with C16TMAOH solution. The acid activation caused a reduction in the number of cation exchange sites, and hence improved the exfoliation of the silicate sheets at higher pH values. The basal spacing increased significantly from 2.20 to 4.01 nm, and depended on the a/c ratios. The acid-activated clays with a/c ratios greater than 0.3 adsorbed significant amounts of C16TMA cations with a basal spacing of 4.01 nm compared with the non-acid-activated montmorillonite (2.51 nm). Meanwhile, the treatment of NaOH solution yielded clays with similar properties to that of the raw used clay. The XRF data, FT-IR, and ²⁹Si MAS-NMR techniques confirmed that the resulting amorphous silica during the acid activation was dissolved, and accompanied by a dramatical reduction in the surface areas. Similar amounts of C16TMA cations were adsorbed, i.e., close to 1 mmol g^?1, with a single basal spacing of 2.52 nm, independently of the treated acid-activated clays. The in-situ powder XRD studies revealed that an increase of the basal spacing to 4.20 nm was observed at intermediate temperatures ranging from 50 to 150 °C for organo-acid-activated clays with basal spacing of 4.01 nm, while a continuous decrease of the basal spacing was observed for organoclays with a basal spacing of 2.52 nm. At higher temperatures greater than 250 °C, the decomposition of the surfactant occurs, and the basal spacing decreases to a value of about 1.4 nm.     

Use of thermal analysis to predict the conditions for thermal explosion to occur: application to a Ce triethanolamine complex

Journal of Thermal Analysis and Calorimetry - Thermal energy storage (TES) has been identified as a breakthrough concept in development of renewable technologies. However, the main challenges are...     

A Comparative Study of Various Pretreatment Approaches for Bio-Ethanol Production from Willow Sawdust,Using Co-Cultures and Mono-Cultures of Different Yeast Strains

The effect of different pretreatment approaches based on alkali (NaOH)/hydrogen peroxide (H₂O₂) on willow sawdust (WS) biomass, in terms of delignification efficiency, structural changes of lignocellulose and subsequent fermentation toward ethanol, was investigated. Bioethanol production was carried out using the conventional yeast Saccharomyces cerevisiae, as well as three non-conventional yeasts strains, i.e., Pichia stipitis, Pachysolen tannophilus, Wickerhamomyces anomalus X19, separately and in co-cultures. The experimental results showed that a two-stage pretreatment approach (NaOH (0.5% w/v) for 24 h and H₂O₂ (0.5% v/v) for 24 h) led to higher delignification (38.3 ± 0.1%) and saccharification efficiency (31.7 ± 0.3%) and higher ethanol concentration and yield. Monocultures of S. cerevisiae or W. anomalus X19 and co-cultures with P. stipitis exhibited ethanol yields in the range of 11.67 ± 0.21 to 13.81 ± 0.20 g/100 g total solids (TS). When WS was subjected to H₂O₂ (0.5% v/v) alone for 24 h, the lowest ethanol yields were observed for all yeast strains, due to the minor impact of this treatment on the main chemical and structural WS characteristics. In order to decide which is the best pretreatment approach, a detailed techno-economical assessment is needed, which will take into account the ethanol yields and the minimum processing cost.     

A variance-based method to rank input variables of the Mesh Adaptive Direct Search algorithm

The Mesh Adaptive Direct Search algorithm (Mads) algorithm is designed for nonsmooth blackbox optimization problems in which the evaluation of the functions defining the problems are expensive to compute. The Mads algorithm is not designed for problems with a large number of variables. The present paper uses a statistical tool based on variance decomposition to rank the relative importance of the variables. This statistical method is then coupled with the Mads algorithm so that the optimization is performed either in the entire space of variables or in subspaces associated with statistically important variables. The resulting algorithm is called Stats-Mads and is tested on bound constrained test problems having up to 500 variables. The numerical results show a significant improvement in the objective function value after a fixed budget of function evaluations.     

Crystal structure and electrical properties study of 4-aminopyridinium chloridobismuthate (III) (C5N2H7)4.HBi2Cl11

The crystal structure of (C₅N₂H₇)₄.HBi₂Cl₁₁ has been determined at room temperature by single crystal X-ray diffraction. The compound crystallizes in the triclinic system with Pī space group. The crystal structure consists of two asymmetric inequivalent molecules of 4-aminopyridinium and anionic HBi₂Cl₁₁ chains. The HBi₂Cl₁₁ anionic chains stacked along the a-axis are formed with Bi₂Cl₁₁ dimers connected to each other via hydrogen atoms. The crystal packing is stabilized with N–H...Cl hydrogen bonds connecting aminopyridinium units to the HBi₂Cl₁₁ anionic chains. The title compound exhibits an order–disorder phase transition at 338 K. The AC electrical conductivity properties of (C₅N₂H₇)₄.HBi₂Cl₁₁ compound have been investigated by means of impedance spectroscopy measurements over wide ranges of frequencies and temperatures, 200 Hz to 5 MHz and 303 to 418 K, respectively. Detailed analysis of the impedance spectrum suggests that the electrical properties of the material are strongly temperature dependent. The frequency-dependent conductivity data were fitted in the Jonscher's law: $ \sigma \left( \omega \right) = \sigma (0) + A{\omega^n} $ . The nature of variation of DC conductivity suggests Arrhenius type of electrical conductivity.     

Some Generalized q-Bessel Type Wavelets and Associated Transforms

In this paper wavelet functions are introduced in the context of q-theory.We precisely extend the case of Bessel and q-Bessel wavelets to the generalized q-Bessel wavelets.Starting from the(q,v)-extension(v =(α,β)) of the q-case,associated generalized q-wavelets and generalized q-wavelet transforms are developed for the new context.Reconstruction and Placherel type formulas are proved.     

Dealing with external actions in belief causal networks

Graphical models are efficient and simple ways to represent dependencies between variables. We introduce in this paper the so-called belief causal networks where dependencies are uncertain causal links and where the uncertainty is represented by belief masses. Through these networks, we propose to represent the results of passively observing the spontaneous behavior of the system and also evaluate the effects of external actions. Interventions are very useful for representing causal relations, we propose to compute their effects using a generalization of the “do” operator. Even if the belief chain rule is different from the Bayesian chain rule, we show that the joint distributions of the altered structures to graphically describe interventions are equivalent. This paper also addresses new issues that are arisen when handling interventions: we argue that in real world applications, external manipulations may be imprecise and show that they have a natural encoding under the belief function framework.