Optineurin downregulation induces endoplasmic reticulum stress, chaperone-mediated autophagy, and apoptosis in pancreatic cancer cells

Pancreatic ductal adenocarcinoma (PDAC) shows a high level of basal autophagy. Here we investigated the role of optineurin (OPTN) in PDAC cell lines, which is a prominent member of the autophagy system. To that purpose, mining of publically available databases showed that OPTN is highly expressed in PDAC and that high levels of expression are related to reduced survival. Therefore, the role of OPTN on proliferation, migration, and colony formation was investigated by transient knockdown in Miapaca, BXPC3, and Suit2-007 human PDAC cells. Furthermore, gene expression modulation in response to OPTN knockdown was assessed by microarray. The influence on cell cycle distribution and cell death signaling cascades was followed by FACS, assays for apoptosis, RT-PCR, and western blot. Finally, autophagy and ROS induction were screened by acridine orange and DCFH-DA fluorescent staining respectively. OPTN knockdown caused significant inhibition of colony formation, increased migration and no significant effect on proliferation in Miapaca, BXPC3 and Suit2-007 cells. The microarray showed modulation of 293 genes in Miapaca versus 302 in Suit2-007 cells, of which 52 genes overlapped. Activated common pathways included the ER stress response and chaperone-mediated autophagy, which was confirmed at mRNA and protein levels. Apoptosis was activated as shown by increased levels of cleaved PARP, Annexin V binding and nuclear fragmentation. OPTN knockdown caused no increased vacuole formation as assessed by acridine orange. Also, there was only marginally increased ROS production. Combination of OPTN knockdown with the autophagy inducer erufosine or LY294002, an inhibitor of autophagy, showed additive effects, which led us to hypothesize that they address different pathways. In conclusion, OPTN knockdown was related to activation of ER stress response and chaperone-mediated autophagy, which tend to confine the damage caused by OPTN knockdown and thus question its value for PDAC therapy

A comparison of the adomian and homotopy perturbation methods in solving the problem of squeezing flow between two circular plates

The objective of this paper is to compare two methods employed for solving nonlinear problems, namely the Adomian Decomposition Method (ADM) and the Homotopy Perturbation Method (HPM). To this effect we solve the Navier‐Stokes equations for the unsteady flow between two circular plates approaching each other symmetrically. The comparison between HPM and ADM is bench‐marked against a numerical solution. The results show that the ADM is more reliable and efficient than HPM from a computational viewpoint. The ADM requires slightly more computational effort than the HPM, but it yields more accurate results than the HPM. First published online: 10 Feb 201

FORMULATION AND CHARACTERIZATION OF FLUCONAZOLE LOADED OLIVE OIL NANOEMULSIONS

Present study was carried out to develop and evaluate olive oil based nano-emulsion for transdermal delivery of fluconazole, a bistriazole based antifungal agent with poor water solubility and lipophilicity. Olive oil, a natural non-irritating, non-toxic proposed permeation enhancer, is known to have some antifungal activity as well. Screening of common emulsifiers like Tweens (Tween 20, tween 60, tween 80), Spans (span 60, span 80), brij 35, puronic 127, and poloxamer 188 were done based on solubility of fluconazole in these surfactants followed by their efficiency to emulsify olive oil in water. Co-emulsifiers such as glycols (polyethylene glycol 200, polyethylene glycol 400, propylene glycol), and short chain alcohols (ethanol, propanol, butanol and octanol) were also screened similarly. Tween 80 and butanol were selected as emulsifier and co-emulsifier respectively to formulate nano-emulsion by aqueous titration method. However, separation was observed after 24 hours. Therefore, span 80 was added as an auxiliary emulsifier to improve emulsification efficiency. Finally, a blend of tween 80, span 80 and butanol was optimized as emulsifier (56 % wt/wt) to emulsify 9 % wt/wt of olive oil in 33 % wt/wt water. Pseudo-ternary phase diagram was employed to identify and optimize the components. Optimized formulation based on phase separation and thermokinetic stability was characterized for globule size, size distribution, zeta potential, viscosity, refractive index and pH. Globule size analysis by zetasizer nano ZS was further confirmed by transmission electron microscopy. Permeation flux of fluconazole from optimized formulation through artificial skin was approximately three fold higher than the control. In conclusion, developed olive oil based nano-emulsion of fluconazole demonstrated promising solubility, permeability and stability. Keywords: Fluconazole, olive oil, nano-emulsion, transdermal permeatio

Estimation method for determining surface film conductance during cooling of fish packages.

This paper presents an alternative method for determining the surface film conductance of an infinite fish slab subjected to the cooling process. Many methods have been published, but their solutions have inherent appreciable inaccuracy and limitations. The present authors used the temperature histories of five locations within a slab sample of fish, obtained by the experimental investigation part of this work, along with the inverse heat conduction problem (IHCP) technique to develop a correlation for variable surface film conductance. When the above correlation was used for temperature predictions, the predicted and experimentally measured temperature distribution profiles were compared numerically. Better agreement than that implemented by other investigators was achieved. This revealed the accuracy and superiority of the present method, and the limitations of other methods are overcome in this method

Machine Learning based Energy Management Model for Smart Grid and Renewable Energy Districts

The combination of renewable energy sources and prosumer-based smart grid is a sustainable solution to cater to the problem of energy demand management. A pressing need is to develop an efficient Energy Management Model (EMM) that integrates renewable energy sources with smart grids. However, the variable scenarios and constraints make this a complex problem. Machine Learning (ML) methods can often model complex and non-linear data better than the statistical models. Therefore, developing an ML algorithm for the EMM is a suitable option as it reduces the complexity of the EMM by developing a single trained model to predict the performance parameters of EMM for multiple scenarios. However, understanding latent correlations and developing trust in highly complex ML models for designing EMM within the stochastic prosumer-based smart grid is still a challenging task. Therefore, this paper integrates ML and Gaussian Process Regression (GPR) in the EMM. At the first stage, an optimization model for Prosumer Energy Surplus (PES), Prosumer Energy Cost (PEC), and Grid Revenue (GR) is formulated to calculate base performance parameters (PES, PEC, and GR) for the training of the ML-based GPR model. In the second stage, stochasticity of renewable energy sources, load, and energy price, same as provided by the Genetic Algorithm (GA) based optimization model for PES, PEC, and GR, and base performance parameters act as input covariates to produce a GPR model that predicts PES, PEC, and GR. Seasonal variations of PES, PEC, and GR are incorporated to remove hitches from seasonal dynamics of prosumers energy generation and prosumers energy consumption. The proposed adaptive Service Level Agreement (SLA) between energy prosumers and the grid benefits both these entities. The results of the proposed model are rigorously compared with conventional optimization (GA and PSO) based EMM to prove the validity of the proposed model

Blockchain enabled data security in vehicular networks

Recently, researchers have applied blockchain technology in vehicular networks to take benefit of its security features, such as confidentiality, authenticity, immutability, integrity, and non-repudiation. The resource-intensive nature of the blockchain consensus algorithm makes it a challenge to integrate it with vehicular networks due to the time-sensitive message dissemination requirements. Moreover, most of the researchers have used the Proof-of-Work consensus algorithm, or its variant to add a block to a blockchain, which is a highly resource-intensive process with greater latency. In this paper, we propose a consensus algorithm for vehicular networks named as Vehicular network Based Consensus Algorithm (VBCA) to ensure data security across the network using blockchain that maintains a secured pool of confirmed messages exchanged in the network. The proposed scheme, based on a consortium blockchain, reduces average transaction latency, and increases the number of confirmed transactions in a decentralized manner, without compromising the integrity and security of data. The simulation results show improved performance in terms of confirmed transactions, transaction latency, number of blocks, and block creation time

Influence of Incomplete Fusion Reaction on Complete Fusion Below 10 Mev/ Nucleon Energies

An attempt has been made in the present work to provide an ample opportunity to explore the information about the influence of incomplete fusion (ICF) reaction dynamics on complete fusion in heavy ion induced nuclear reactions. excitation functions for several evaporation residues produced in the interaction of projectile 16O with target 175lu have been measured over the wide projectile energy range ≈ 70-100 MeV. the recoil-catcher activation technique followed by the offline γ-ray spectroscopy has been used for the present measurements. In case of precursor decay, we have made use of Cavinato et al. formulation to calculate the independent cross-section of the identified residues. the measured efs are compared with theoretical predictions of statistical model code PACE-2 and any enhancement in the measured cross-section from theoretical prediction may be due to ICF reaction process. An attempt has been made to estimate the ICf contribution of the cross-section from the measured excitation function data and the dependence of ICf cross-section on projectile energy

Efficacy of biological agents and fillers seed coating in improving drought stress in anise

Many plants, including anise, have tiny, non-uniform seeds with low and light nutrient reserves. The seeds also show a weak establishment, especially under stressful conditions where their accurate planting in the soil and optimal yield are tough. This study sought to improve anise seeds' physical and physiological characteristics under drought stress. To this end, two factorial experiments under laboratory and greenhouse conditions were performed in a completely randomized design with 4 and 3 replications, respectively. Five levels of seed inoculation (inoculation with T36 and T43 of Trichoderma harzianum, and CHA0 and B52 of Pseudomonas fluorescent, and non-inoculation which means that control seeds were not treated with microbial inoculant), three levels of coating (K10P20, K10P10V5, and non-coating), and three levels of drought stress (0, -3, and -6 bars) were considered as the factorial experiment [vermiculite (V), kaolin (K), and perlite (P) numbers refer to the amount of material used in grams]. The laboratory experiment revealed that the combined treatments of bio-agents with coating increased the physical and germination characteristics of anise seeds compared to the control treatment. The greenhouse experiment showed that drought stress reduced the initial growth indices. Still, the combination treatments of biological agents and coating (fillers) could alleviate the destructive effects of drought stress to some extent and improve these indices. The best treatment was provided by T36 and K10P20 in both experiments, which significantly increased morphological indices.Peer reviewe

Regulation of the Stem Cell–Host Immune System Interplay Using Hydrogel Coencapsulation System with an Anti-Inflammatory Drug

The host immune system is known to influence mesenchymal stem cell (MSC)-mediated bone tissue regeneration. However, the therapeutic capacity of hydrogel biomaterial to modulate the interplay between MSCs and T-lymphocytes is unknown. Here it is shown that encapsulating hydrogel affects this interplay when used to encapsulate MSCs for implantation by hindering the penetration of pro-inflammatory cells and/or cytokines, leading to improved viability of the encapsulated MSCs. This combats the effects of the host pro-inflammatory T-lymphocyte-induced nuclear factor kappaB pathway, which can reduce MSC viability through the CASPASE-3 and CAS-PASE-8 associated proapoptotic cascade, resulting in the apoptosis of MSCs. To corroborate rescue of engrafted MSCs from the insult of the host immune system, the incorporation of the anti-inflammatory drug indomethacin into the encapsulating alginate hydrogel further regulates the local microenvironment and prevents pro-inflammatory cytokine-induced apoptosis. These findings suggest that the encapsulating hydrogel can regulate the MSC-host immune cell interplay and direct the fate of the implanted MSCs, leading to enhanced tissue regeneration