Evaluating the effect of foeniculum vulgar on scopolamin-induced memory impairment in Male Mice

Background: Estrogen is a steroid that regardless of its obvious effects on females’ reproductive functions shows beneficial effects on cognition. Foeniculum vulgar (fennel) has phytoestrogen compounds that might be beneficial in memory performance. This research was performed to understand if this plant can improve memory. Methods: To evaluate memory, novel object recognition task was used in male Balb-c mice, which comprised of three sections: habituation, learning trial (T1) and the test trial (T2). In this method, the difference in the exploration time between a familial (F) and a novel (N) object is taken as an index of memory performance [recognition index (RI) = (N – F)/(N + F) × 100]. Findings: Memory was harmed using 0.5 mg/kg subcutaneous scopolamine [RI (%) = -16.0 ± 3.0]. 50 mg/kg intraperitoneal fennel considerably prevented memory impairment of scopolamine [RI (%) = 35.0 ± 7.1] and this was parallel with the memory index in normal animals [RI (%) = 50.0 ± 5.8]. In addition, 0.2 mg/kg intraperitoneal 17-β estradiol showed similar results as fennel on memory protection [RI (%) = 36.0 ± 6.6]. However, the beneficial effects of fennel were impaired by prior intraperitoneal injection of 1 mg/kg tamoxifen [RI (%) = -29.0 ± 7.1]. Conclusion: The beneficial effect of fennel on memory is achieved by estrogenic receptors present in the brain; by stimulating these receptors, they could cause an increase in acetylcholine release. Therefore, it can competitively prevent the antagonizing effect of scopolamine on cholinergic receptors. © 2015, Isfahan University of Medical Sciences(IUMS). All rights reserved. Evaluating the effect of foeniculum vulgar on scopolamin-induced memory impairment in Male Mice. Available from: https://www.researchgate.net/publication/282273930_Evaluating_the_effect_of_foeniculum_vulgar_on_scopolamin-induced_memory_impairment_in_Male_Mice [accessed Jul 29, 2017]

Evaluating the analgesic effect of Cucurbita maxima Duch hydro-alcoholic extract in rats

Background and aims: Cucurbita maxima Duch (CMD) is used as sedative for tooth and ear pain, but its analgesic effect has not been research in experimental studies. The aim of this study was to investigate the analgesic effect of hydro-alcoholic extract of CMD was studied using formalin model in rats. Methods: In this experimental study, 60 Rats were randomly divided into 6 equal groups. Control group was injected distilled water and three experimental groups were injected CMD extracts (50, 100 and 200 mg/kg). Group 5 received ibuprofen and group 6 received naloxone with the most effective dose of the extract. Extract or drugs were injected 15 minutes before formalin injection. The responses of animals to pain were recorded for 30 min. after the formalin injection. Responses of first 0-5 min. were considered as acute pain and responses of 15-30 min. as chronic pain. Results: CRM extracts reduced acute pain in doses of 100 and 200 mg/kg (P<0.001). In addition, the extract decreased chronic pain in all used concentrations compared to the control group (P<0.001). Naloxone inhibited analgesic effect of the extract (P<0.05). Conclusion: CRM extracts reduce acute and chronic pains in formalin test through opioid system and it might be used as an analgesic drug

Growth and Post-Deposition Treatments of SrTiO3 Films for Dye-Sensitized Photoelectrosynthesis Cell Applications

Sensitized SrTiO3 films were evaluated as potential photoanodes for dye-sensitized photoelectrosynthesis cells (DSPECs). The SrTiO3 films were grown via pulsed laser deposition (PLD) on a transparent conducting oxide (fluorine-doped tin oxide, FTO) substrate, annealed, and then loaded with zinc(II) 5,10,15-tris(mesityl)-20-[(dihydroxyphosphoryl)phenyl] porphyrin (MPZnP). When paired with a platinum wire counter electrode and an Ag/AgCl reference electrode these sensitized films exhibited photocurrent densities on the order of 350 nA/cm2 under 0 V applied bias conditions versus a normal hydrogen electrode (NHE) and 75 mW/cm2 illumination at a wavelength of 445 nm. The conditions of the post-deposition annealing step - namely, a high-temperature reducing atmosphere - proved to be the most important growth parameters for increasing photocurrent in these electrodes

Dye-Sensitized Nonstoichiometric Strontium Titanate Core-Shell Photocathodes for Photoelectrosynthesis Applications

A core-shell approach that utilizes a high-surface-area conducting core and an outer semiconductor shell is exploited here to prepare p-type dye-sensitized solar energy cells that operate with a minimal applied bias. Photocathodes were prepared by coating thin films of nanocrystalline indium tin oxide with a 0.8 nm Al2O3 seeding layer, followed by the chemical growth of nonstoichiometric strontium titanate. Films were annealed and sensitized with either a porphyrin chromophore or a chromophore-catalyst molecular assembly consisting of the porphyrin covalently tethered to the ruthenium complex. The sensitized photoelectrodes produced cathodic photocurrents of up to -315 μA/cm2 under simulated sunlight (AM1.5G, 100 mW/cm2) in aqueous media, pH 5. The photocurrent was increased by the addition of regenerative hole donors to the system, consistent with slow interfacial recombination kinetics, an important property of p-type dye-sensitized electrodes

Crossing the divide between homogeneous and heterogeneous catalysis in water oxidation

An atomic layer deposition (ALD) procedure is described for stabilizing surface binding of a water oxidation catalyst to the surfaces of nanostructured films of indium tin oxide. The catalyst is stabilized on the surface of electrodes by ALD of an overlayer of TiO2. Stabilization of surface binding allows use of basic solutions where a rate enhancement for water oxidation of ∼106 is observed compared with acidic conditions. There are important implications for stabilizing surface-bound molecular assemblies for applications in dye sensitized solar cells, electrocatalysis, and photoelectrocatalysis

Solar water splitting in a molecular photoelectrochemical cell

Solar water splitting into H2 and O2 with visible light has been achieved by a molecular assembly. The dye sensitized photoelectrosynthesis cell configuration combined with core–shell structures with a thin layer of TiO2 on transparent, nanostructured transparent conducting oxides (TCO), with the outer TiO2 shell formed by atomic layer deposition. In this configuration, excitation and injection occur rapidly and efficiently with the injected electrons collected by the nanostructured TCO on the nanosecond timescale where they are collected by the planar conductive electrode and transmitted to the cathode for H2 production. This allows multiple oxidative equivalents to accumulate at a remote catalyst where water oxidation catalysis occurs

Evaluation of anti-depression, antioxidant and motor coordination effects of Cucurbita Maxima Duch hydro-alcoholic extract in rats

Abstract Objectives: In traditional medicine, Cucurbita maxima Duch is known as a sedating plant. In Islamic medicine, this plant is widely used for the treatment of depression. This study aimed to evaluate the anti-depression, antioxidant and motor coordination effects of this medicinal herb. Materials and Methods: In this study, hydroalcoholic extract of Cucurbita maxima Duch was prepared using maceration methods, and animals were divided into four groups. Control subjects received normal saline, and experimental subjects received the

Using Artificial Intelligence for Predicting the Duration of Emergency Evacuation During Hospital Fire

Objective: A danger threatening hospitals is fire. The most important action following a fire is to urgently evacuate the hospital during the shortest time possible. The aim of this study was to predict the duration of emergency evacuation following hospital fire using machine-learning algorithms. Methods: In this study, the real emergency evacuation duration of 190 patients admitted to a hospital was predicted in a simulation based on the following 8 factors: the number of hospital floors, patient preparation and transfer time, distance to the safe location, as well as patient's weight, age, sex, and movement capability. To design and validate the model, we used statistical models of machine learning, including Support Vector Machines Random Forest, Naive Bayes Classifier, and Artificial Neural Network. Results: Data analysis showed that based on the Area Under the Curve, precision, and sensitivity values of 99.5, 92.4, and 92.1, respectively, the Random Forest model showed a better performance compared to other models for predicting the duration of hospital emergency evacuation during fire. Conclusion: Predicting evacuation duration can provide managers with accurate information and true analyses of these events. Therefore, health policy makers and managers can promote preparedness and responsiveness during fire by predicting evacuation duration and developing appropriate plans using machine learning models